2014-03-28
A formal ontology in the domain of biological and clinical statistics
Jie Zheng
Marcy Harris
OBCS stands for the Ontology of Biological and Clinical Statistics. OBCS is an ontology in the domain of biological and clinical statistics. It is aligned with the Basic Formal Ontology (BFO) and the Ontology for Biomedical Investigations (OBI). OBCS imports all possible biostatistics terms in OBI and includes many additional biostatistics terms, some of which were proposed and discussed in the OBI face-to-face workshop in Ann Arbor in 2012.
OBCS: Ontology of Biological and Clinical Statistics
OWL-DL
Version: 1.0.16
Yongqun "Oliver" He
NIAID GSCID-BRC alternative term
An alternative term used by the National Institute of Allergy and Infectious Diseases (NIAID) Genomic Sequencing Centers for Infectious Diseases (GSCID) and Bioinformatics Resource Centers (BRC).
NIAID GSCID-BRC alternative term
NIAID GSCID-BRC metadata working group
PERSON: Chris Stoeckert, Jie Zheng
IEDB alternative term
An alternative term used by the IEDB.
IEDB
IEDB alternative term
PERSON:Randi Vita, Jason Greenbaum, Bjoern Peters
Description
Description
An account of the content of the resource.
Description may include but is not limited to: an abstract,
table of contents, reference to a graphical representation
of content or a free-text account of the content.
definition
textual definition
definition
definition
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
The official OBI definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions.
The official definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions.
definition
PERSON:Daniel Schober
editor note
An administrative note intended for its editor. It may not be included in the publication version of the ontology, so it should contain nothing necessary for end users to understand the ontology.
GROUP:OBI:<http://purl.obfoundry.org/obo/obi>
PERSON:Daniel Schober
editor note
imported from
For external terms/classes, the ontology from which the term was imported
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
PERSON:Alan Ruttenberg
PERSON:Melanie Courtot
imported from
has curation status
OBI_0000281
PERSON:Alan Ruttenberg
PERSON:Bill Bug
PERSON:Melanie Courtot
has curation status
curator note
An administrative note of use for a curator but of no use for a user
PERSON:Alan Ruttenberg
curator note
definition source
Discussion on obo-discuss mailing-list, see http://bit.ly/hgm99w
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
PERSON:Daniel Schober
definition source
formal citation, e.g. identifier in external database to indicate / attribute source(s) for the definition. Free text indicate / attribute source(s) for the definition. EXAMPLE: Author Name, URI, MeSH Term C04, PUBMED ID, Wiki uri on 31.01.2007
term editor
20110707, MC: label update to term editor and definition modified accordingly. See http://code.google.com/p/information-artifact-ontology/issues/detail?id=115.
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
Name of editor entering the term in the file. The term editor is a point of contact for information regarding the term. The term editor may be, but is not always, the author of the definition, which may have been worked upon by several people
PERSON:Daniel Schober
term editor
alternative term
An alternative name for a class or property which means the same thing as the preferred name (semantically equivalent)
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
PERSON:Daniel Schober
alternative term
Source
Source
A reference to a resource from which the present resource
is derived.
The present resource may be derived from the Source resource
in whole or in part. Recommended best practice is to reference
the resource by means of a string or number conforming to a
formal identification system.
editor preferred label
editor preferred term
editor preferred term
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
PERSON:Daniel Schober
The concise, meaningful, and human-friendly name for a class or property preferred by the ontology developers. (US-English)
editor preferred label
example of usage
A phrase describing how a class name should be used. May also include other kinds of examples that facilitate immediate understanding of a class semantics, such as widely known prototypical subclasses or instances of the class. Although essential for high level terms, examples for low level terms (e.g., Affymetrix HU133 array) are not
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
PERSON:Daniel Schober
example of usage
ISA alternative term
Requested by Alejandra Gonzalez-Beltran
https://sourceforge.net/tracker/?func=detail&aid=3603413&group_id=177891&atid=886178
ISA alternative term
Person: Philippe Rocca-Serra
Person: Alejandra Gonzalez-Beltran
ISA tools project (http://isa-tools.org)
An alternative term used by the ISA tools project (http://isa-tools.org).
is part of
There is controversy about this relation intended to represent the relation between some arbitrary physical thing that is used as a represention/proxy/pointer to something else
is part of
part of
part_of
has part
has part
has_part
inheres in
inheres in
inheres_in
is bearer of
bearer of
bearer_of
is bearer of
is realized by
is realized by
realized by
realized_by
realizes
realizes
participates in
participates in
participates_in
has participant
has participant
has_participant
is concretized as
is concretized as
concretizes
concretizes
is immediately preceded by
immediately preceded by
immediately_preceded_by
is immediately preceded by
is preceded by
is preceded by
preceded by
preceded_by
s depends on
s depends on
s_depends_on
is role of
is role of
role of
role_of
is located in
is located in
located in
located_in
has role
has role
has_role
has measurement unit label
A relation between a value specification and its unit of measurement.
has measurement unit label
is about
7/6/2009 Alan Ruttenberg. Following discussion with Jonathan Rees, and introduction of "mentions" relation. Weaken the is_about relationship to be primitive.
We will try to build it back up by elaborating the various subproperties that are more precisely defined.
Some currently missing phenomena that should be considered "about" are predications - "The only person who knows the answer is sitting beside me" , Allegory, Satire, and other literary forms that can be topical without explicitly mentioning the topic.
Smith, Ceusters, Ruttenberg, 2000 years of philosophy
This document is about information artifacts and their representations
is about
is_about is a (currently) primitive relation that relates an information artifact to an entity.
person:Alan Ruttenberg
denotes
2009-11-10 Alan Ruttenberg. Old definition said the following to emphasize the generic nature of this relation. We no longer have 'specifically denotes', which would have been primitive, so make this relation primitive.
g denotes r =def
r is a portion of reality
there is some c that is a concretization of g
every c that is a concretization of g specifically denotes r
A person's name denotes the person. A variable name in a computer program denotes some piece of memory. Lexically equivalent strings can denote different things, for instance "Alan" can denote different people. In each case of use, there is a case of the denotation relation obtaining, between "Alan" and the person that is being named.
Conversations with Barry Smith, Werner Ceusters, Bjoern Peters, Michel Dumontier, Melanie Courtot, James Malone, Bill Hogan
denotes
denotes is a primitive, instance-level, relation obtaining between an information content entity and some portion of reality. Denotation is what happens when someone creates an information content entity E in order to specifically refer to something. The only relation between E and the thing is that E can be used to 'pick out' the thing. This relation connects those two together. Freedictionary.com sense 3: To signify directly; refer to specifically
person:Alan Ruttenberg
is quality measurement of
8/6/2009 Alan Ruttenberg: The strategy is to be rather specific with this relationship. There are other kinds of measurements that are not of qualities, such as those that measure time. We will add these as separate properties for the moment and see about generalizing later
Alan Ruttenberg
From the second IAO workshop [Alan Ruttenberg 8/6/2009: not completely current, though bringing in comparison is probably important]
This one is the one we are struggling with at the moment. The issue is what a measurement measures. On the one hand saying that it measures the quality would include it "measuring" the bearer = referring to the bearer in the measurement. However this makes comparisons of two different things not possible. On the other hand not having it inhere in the bearer, on the face of it, breaks the audit trail.
Werner suggests a solution based on "Magnitudes" a proposal for which we are awaiting details.
--
From the second IAO workshop, various comments, [commented on by Alan Ruttenberg 8/6/2009]
unit of measure is a quality, e.g. the length of a ruler.
[We decided to hedge on what units of measure are, instead talking about measurement unit labels, which are the information content entities that are about whatever measurement units are. For IAO we need that information entity in any case. See the term measurement unit label]
[Some struggling with the various subflavors of is_about. We subsequently removed the relation represents, and describes until and only when we have a better theory]
a represents b means either a denotes b or a describes
describe:
a describes b means a is about b and a allows an inference of at least one quality of b
We have had a long discussion about denotes versus describes.
From the second IAO workshop: An attempt at tieing the quality to the measurement datum more carefully.
a is a magnitude means a is a determinate quality particular inhering in some bearer b existing at a time t that can be represented/denoted by an information content entity e that has parts denoting a unit of measure, a number, and b. The unit of measure is an instance of the determinable quality.
From the second meeting on IAO:
An attempt at defining assay using Barry's "reliability" wording
assay:
process and has_input some material entity
and has_output some information content entity
and which is such that instances of this process type reliably generate
outputs that describes the input.
This one is the one we are struggling with at the moment. The issue is what a measurement measures. On the one hand saying that it measures the quality would include it "measuring" the bearer = referring to the bearer in the measurement. However this makes comparisons of two different things not possible. On the other hand not having it inhere in the bearer, on the face of it, breaks the audit trail.
Werner suggests a solution based on "Magnitudes" a proposal for which we are awaiting details.
is quality measurement of
m is a quality measurement of q at t when
q is a quality
there is a measurement process p that has specified output m, a measurement datum, that is about q
has coordinate unit label
has coordinate unit label
relating a cartesian spatial coordinate datum to a unit label that together with the values represent a point
is duration of
Person:Alan Ruttenberg
is duration of
relates a process to a time-measurement-datum that represents the duration of the process
has time stamp
Alan Ruttenberg
has time stamp
relates a time stamped measurement datum to the time measurement datum that denotes the time when the measurement was taken
has measurement datum
Alan Ruttenberg
has measurement datum
relates a time stamped measurement datum to the measurement datum that was measured
is_supported_by_data
Philly 2011 workshop
The relation between a data item and a conclusion where the conclusion is the output of a data interpreting process and the data item is used as an input to that process
The relation between the conclusion "Gene tpbA is involved in EPS production" and the data items produced using two sets of organisms, one being a tpbA knockout, the other being tpbA wildtype tested in polysacharide production assays and analyzed using an ANOVA.
is_supported_by_data
OBI
OBI
has_specified_input
8/17/09: specified inputs of one process are not necessarily specified inputs of a larger process that it is part of. This is in contrast to how 'has participant' works.
PERSON: Bjoern Peters
PERSON: Larry Hunter
PERSON: Melanie Coutot
A relation between a planned process and a continuant participating in that process that is not created during the process. The presence of the continuant during the process is explicitly specified in the plan specification which the process realizes the concretization of.
PERSON: Alan Ruttenberg
has_specified_input
see is_input_of example_of_usage
has_specified_output
PERSON: Bjoern Peters
PERSON: Larry Hunter
PERSON: Melanie Courtot
A relation between a planned process and a continuant participating in that process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of.
PERSON: Alan Ruttenberg
has_specified_output
is_specified_output_of
PERSON:Bjoern Peters
A relation between a planned process and a continuant participating in that process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of.
Alan Ruttenberg
is_specified_output_of
achieves_planned_objective
A cell sorting process achieves the objective specification 'material separation objective'
BP, AR, PPPB branch
PPPB branch derived
This relation obtains between a planned process and a objective specification when the criteria specified in the objective specification are met at the end of the planned process.
achieves_planned_objective
modified according to email thread from 1/23/09 in accordince with DT and PPPB branch
has category label
has category label
A relation between a categorical measurement data item and the categorical label that indicates the value of that data item on the categorical scale.
has value specification
has value specification
PERSON: James A. Overton
OBI
A relation between an information content entity and a value specification that specifies its value.
temporal relation
move to BFO?
A relation that holds between two occurrents. This is a grouping relation that collects together all the Allen relations.
Allen
temporal relation
starts
inverse of starts with
Chris Mungall
Allen
starts
has measurement value
The range should probably not be restricted to "float". It makes sense to set it to "real". However we do not know how this change will affect SPARQL queries, so we have left the range as-is for now.
A relation between a scalar measurement data item and a number that quantifies it.
has measurement value
has x coordinate value
has x coordinate value
has z coordinate value
has z coordinate value
has y coordinate value
has y coordinate value
has_feature_value
James Malone
has_feature_value
has_feature_value datatype property is used to describe the feature values which the feature class can contain, for example has_base can have feature values of nonNegativeInteger values.
has specified value
OBI
A relation between a value specification and a number that quantifies it.
PERSON: James A. Overton
A range of 'real' might be better than 'float'. For now we follow 'has measurement value' until we can consider technical issues with SPARQL queries and reasoning.
has specified value
entity
entity
continuant
An entity that exists in full at any time in which it exists at all, persists through time while maintaining its identity and has no temporal parts.
a heart
a person
a symphony orchestra
continuant
endurant
the color of a tomato
the disposition of blood to coagulate
the lawn and atmosphere in front of our building
the mass of a cloud
occurrent
An entity that has temporal parts and that happens, unfolds or develops through time. Sometimes also called perdurants.
a surgical operation as processual context for a nosocomical infection
occurrent
perdurant
the life of an organism
the most interesting part of Van Gogh's life
the spatiotemporal context occupied by a process of cellular meiosis
the spatiotemporal region occupied by the development of a cancer tumor
independent continuant
A continuant that is a bearer of quality and realizable entity entities, in which other entities inhere and which itself cannot inhere in anything.
a chair
a heart
a leg
a person
a symphony orchestra
an organism
independent continuant
substantial entity
the bottom right portion of a human torso
the lawn and atmosphere in front of our building
dependent continuant
A continuant that is either dependent on one or other independent continuant bearers or inheres in or is borne by other entities.
dependent continuant
spatial region
A continuant that is neither bearer of quality entities nor inheres in any other entities.
All instances of continuant [snap:Continuant] are spatial entities, that is, they enter in the relation of (spatial) location with spatial region [snap:SpatialRegion] entities. As a particular case, the exact spatial location of a spatial region [snap:SpatialRegion] is this region itself.
An instance of spatial region [snap:SpatialRegion] is a part of space. All parts of space are spatial region [snap:SpatialRegion] entities and only spatial region [snap:SpatialRegion] entities are parts of space. Space is the entire extent of the spatial universe, a designated individual, which is thus itself a spatial region [snap:SpatialRegion].
Space and spatial region [snap:SpatialRegion] entities are entities in their own rights which exist independently of any entities which can be located at them. This view of space is sometimes called "absolutist" or "the container view". In BFO, the class site [snap:Site] allows for a so-called relational view of space, that is to say, a view according to which spatiality is a matter of relative location between entities and not a matter of being tied to space. The bridge between these two views is secured through the fact that while instances of site [snap:Site] are not spatial region [snap:SpatialRegion] entities, they are nevertheless spatial entities.
parts of the sum total of all space in the universe
spatial region
the sum total of all space in the universe
process
A processual entity that is a maximally connected spatiotemporal whole and has bona fide beginnings and endings corresponding to real discontinuities.
process
the life of an organism
the process of cell-division
the process of sleeping
two dimensional region
A spatial region with two dimensions.
the surface of a cube-shaped part of space
the surface of a rectilinear planar figure-shaped part of space
the surface of a sphere-shaped part of space
two dimensional region
disposition
A realizable entity that essentially causes a specific process or transformation in the object in which it inheres, under specific circumstances and in conjunction with the laws of nature. A general formula for dispositions is: X (object has the disposition D to (transform, initiate a process) R under conditions C.
disposition
the disposition of a patient with a weakened immune system to contract disease
the disposition of a vase to brake if dropped
the disposition of blood to coagulate
the disposition of metal to conduct electricity
the disposition of vegetables to decay when not refrigerated
realizable entity
A specifically dependent continuant that inheres in continuant entities and are not exhibited in full at every time in which it inheres in an entity or group of entities. The exhibition or actualization of a realizable entity is a particular manifestation, functioning or process that occurs under certain circumstances.
If a realizable entity [snap:RealizableEntity] inheres in a continuant [snap:Continuant], this does not imply that it is actually realized.
realizable entity
the disposition of blood to coagulate
the disposition of metal to conduct electricity
the function of the reproductive organs
the role of being a doctor
zero dimensional region
A spatial region with no dimensions.
a point
zero dimensional region
quality
A specifically dependent continuant that is exhibited if it inheres in an entity or entities at all (a categorical property).
quality
the ambient temperature of air
the circumference of a waist
the color of a tomato
the mass of a piece of gold
the shape of a nose
the weight of a chimpanzee
specifically dependent continuant
A continuant that inheres in or is borne by other entities. Every instance of A requires some specific instance of B which must always be the same.
mode
property
specifically dependent continuant
the color of a tomato
the disposition of fish to decay
the function of the heart in the body: to pump blood, to receive de-oxygenated and oxygenated blood, etc.
the liquidity of blood
the mass of a cloud
the role of being a doctor
the smell of mozzarella
trope
role
A realizable entity the manifestation of which brings about some result or end that is not essential to a continuant in virtue of the kind of thing that it is but that can be served or participated in by that kind of continuant in some kinds of natural, social or institutional contexts.
role
the role of a biological grandfather as legal guardian in the context of a system of laws
the role of a chemical compound in an experiment
the role of a patient relative as defined by a hospital administrative form
the role of a person as a surgeon
the role of a student in a university
the role of a woman as a legal mother in the context of system of laws
the role of ingested matter in digestion
one dimensional region
A spatial region with one dimension.
an edge of a cube-shaped part of space
one dimensional region
the part of space that is a line stretching from one end of absolute space to the other
three dimensional region
A spatial region with three dimensions.
a cube-shaped part of space
a sphere-shaped part of space
three dimensional region
generically dependent continuant
A continuant that is dependent on one or other independent continuant bearers. For every instance of A requires some instance of (an independent continuant type) B but which instance of B serves can change from time to time.
a certain PDF file that exists in different and in several hard drives
generically dependent continuant
process boundary
A processual entity that is the fiat or bona fide instantaneous temporal process boundary.
birth
death
process boundary
the detaching of a finger in an industrial accident
the final separation of two cells at the end of cell-division
the forming of a synapse
the incision at the beginning of a surgery
the onset of REM sleep
material entity
An independent continuant that is spatially extended whose identity is independent of that of other entities and can be maintained through time.
Examples: collection of random bacteria, a chair, dorsal surface of the body
Material entity [snap:MaterialEntity] subsumes object [snap:Object], fiat object part [snap:FiatObjectPart], and object aggregate [snap:ObjectAggregate], which assume a three level theory of granularity, which is inadequate for some domains, such as biology.
material entity
deoxyribonucleic acid
High molecular weight, linear polymers, composed of nucleotides containing deoxyribose and linked by phosphodiester bonds; DNA contain the genetic information of organisms.
deoxyribonucleic acid
molecular entity
Any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer etc., identifiable as a separately distinguishable entity.
molecular entity
We are assuming that every molecular entity has to be completely connected by chemical bonds. This excludes protein complexes, which are comprised of minimally two separate molecular entities. We will follow up with Chebi to ensure this is their understanding as well
nucleic acid
A macromolecule made up of nucleotide units and hydrolysable into certain pyrimidine or purine bases (usually adenine, cytosine, guanine, thymine, uracil), D-ribose or 2-deoxy-D-ribose and phosphoric acid.
nucleic acid
macromolecule
A macromolecule is a molecule of high relative molecular mass, the structure of which essentially comprises the multiple repetition of units derived, actually or conceptually, from molecules of low relative molecular mass.
macromolecule
polymer
cell
A material entity of anatomical origin (part of or deriving from an organism) that has as its parts a maximally connected cell compartment surrounded by a plasma membrane.
cell
PMID:18089833.Cancer Res. 2007 Dec 15;67(24):12018-25. "...Epithelial cells were harvested from histologically confirmed adenocarcinomas .."
biological_process
Any process specifically pertinent to the functioning of integrated living units: cells, tissues, organs, and organisms. A process is a collection of molecular events with a defined beginning and end.
biological_process
response to stimulus
Any process that results in a change in state or activity of a cell or an organism (in terms of movement, secretion, enzyme production, gene expression, etc.) as a result of a stimulus. The process begins with detection of the stimulus and ends with a change in state or activity or the cell or organism.
response to stimulus
measurement unit label
2009-03-16: provenance: a term measurement unit was
proposed for OBI (OBI_0000176) , edited by Chris Stoeckert and
Cristian Cocos, and subsequently moved to IAO where the objective for
which the original term was defined was satisfied with the definition
of this, different, term.
2009-03-16: review of this term done during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI.
A data item label that denotes a unit of measure.
Examples of measurement unit labels are liters, inches, weight per volume.
PERSON: Alan Ruttenberg
PERSON: Melanie Courtot
measurement unit label
objective specification
2013-09-23 OBI call: Simplify definition by removing following part -
When the objective specification is part of a plan specification, the concretization of the plan specification is realized in a planned process in which the bearer tries to control the world so that the process endpoint is achieved.
2009-03-16: original definition when imported from OBI read: "objective is an
non realizable information entity which can serve as that proper part
of a plan towards which the realization of the plan is directed."
Answers the question, why did you do this experiment?
OBI Plan and Planned Process/Roles Branch
OBI_0000217
PERSON: Alan Ruttenberg
PERSON: Barry Smith
PERSON: Bjoern Peters
PERSON: Jennifer Fostel
a directive information entity that describes an intended process endpoint.
objective specification
the objective of a ChIP assay is to identify protein and DNA interaction
purpose of a study; support of hypothesis, discovery of new information
action specification
Alan Ruttenberg
OBI Plan and Planned Process branch
Pour the contents of flask 1 into flask 2
a directive information entity that describes an action the bearer will take
action specification
data item label
9/22/11 BP: changed the rdfs:label for this class from 'label' to 'datum label' to convey that this class is not intended to cover all kinds of labels (stickers, radiolabels, etc.), and not even all kind of textual labels, but rather the kind of labels occuring in a datum.
An information content entity that is part of some data item and is used to partially define the denotation of that data item.
GROUP: IAO
data item label
datum label
http://www.golovchenko.org/cgi-bin/wnsearch?q=label#4n
information carrier
12/15/09: There is a concern that some ways that carry information may be processes rather than qualities, such as in a 'delayed wave carrier'.
A quality of an information bearer that imparts the information content
In the case of a printed paperback novel the physicality of the ink and of the paper form part of the information bearer. The qualities of appearing black and having a certain pattern for the ink and appearing white for the paper form part of the information carrier in this case.
PERSON: Alan Ruttenberg
Smith, Ceusters, Ruttenberg, 2000 years of philosophy
information carrier
data item
2/2/2009 Alan and Bjoern discussing FACS run output data. This is a data item because it is about the cell population. Each element records an event and is typically further composed a set of measurment data items that record the fluorescent intensity stimulated by one of the lasers.
2009-03-16: data item deliberatly ambiguous: we merged data set and datum to be one entity, not knowing how to define singular versus plural. So data item is more general than datum.
2009-03-16: removed datum as alternative term as datum specifically refers to singular form, and is thus not an exact synonym.
An information content entity that is intended to be a truthful statement about something (modulo, e.g., measurement precision or other systematic errors) and is constructed/acquired by a method that reliably tends to produce (approximately) truthful statements.
Data items include counts of things, analyte concentrations, and statistical summaries.
PERSON: Alan Ruttenberg
PERSON: Chris Stoeckert
PERSON: Jonathan Rees
data
data item
information content entity
Examples of information content entites include journal articles, data, graphical layouts, and graphs.
OBI_0000142
PERSON: Chris Stoeckert
an information content entity is an entity that is generically dependent on some material entity and stands in relation of aboutness to some entity
information content entity
information_content_entity 'is_encoded_in' some digital_entity in obi before split (040907). information_content_entity 'is_encoded_in' some physical_document in obi before split (040907).
Previous. An information content entity is a non-realizable information entity that 'is encoded in' some digital or physical entity.
scalar measurement datum
10 feet. 3 ml.
2009-03-16: we decided to keep datum singular in scalar measurement datum, as in
this case we explicitly refer to the singular form
PERSON: Alan Ruttenberg
PERSON: Melanie Courtot
Would write this as: has_part some 'measurement unit label' and has_part some numeral and has_part exactly 2, except for the fact that this won't let us take advantage of OWL reasoning over the numbers. Instead use has measurment value property to represent the same. Use has measurement unit label (subproperty of has_part) so we can easily say that there is only one of them.
a scalar measurement datum is a measurement datum that is composed of two parts, numerals and a unit label.
scalar measurement datum
directive information entity
2009-03-16: provenance: a term realizable information entity was proposed for OBI (OBI_0000337) , edited by the PlanAndPlannedProcess branch. Original definition was "is the specification of a process that can be
concretized and realized by an actor" with alternative term "instruction".It has been subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definitionof this, different, term.
Philly2013 - AR: What differentiates a directive information entity from an information concretization is that it can have concretizations that are either qualities or realizable entities. The concretizations that are realizable entities are created when an individual chooses to take up the direction, i.e. has the intention to (try to) realize it.
8/6/2009 Alan Ruttenberg: Changed label from "information entity about a realizable" after discussions at ICBO
An information content entity whose concretizations indicate to their bearer how to realize them in a process.
PERSON: Alan Ruttenberg
PERSON: Bjoern Peters
Werner pushed back on calling it realizable information entity as it isn't realizable. However this name isn't right either. An example would be a recipe. The realizable entity would be a plan, but the information entity isn't about the plan, it, once concretized, *is* the plan. -Alan
directive information entity
dot plot
A dot plot is a report graph which is a graphical representation of data where each data point is represented by a single dot placed on coordinates corresponding to data point values in particular dimensions.
Dot plot of SSC-H and FSC-H.
OBI_0000123
dot plot
group:OBI
person:Allyson Lister
person:Chris Stoeckert
graph
A diagram that presents one or more tuples of information by mapping those tuples in to a two dimensional space in a non arbitrary way.
OBI_0000240
PERSON: Lawrence Hunter
graph
group:OBI
person:Alan Ruttenberg
person:Allyson Lister
algorithm
A plan specification which describes inputs, output of mathematical functions as well as workflow of execution for achieving an predefined objective. Algorithms are realized usually by means of implementation as computer programs for execution by automata.
OBI_0000270
PMID: 18378114.Genomics. 2008 Mar 28. LINKGEN: A new algorithm to process data in genetic linkage studies.
Philippe Rocca-Serra
PlanAndPlannedProcess Branch
adapted from discussion on OBI list (Matthew Pocock, Christian Cocos, Alan Ruttenberg)
algorithm
curation status specification
Better to represent curation as a process with parts and then relate labels to that process (in IAO meeting)
GROUP:OBI:<http://purl.obolibrary.org/obo/obi>
OBI_0000266
PERSON:Bill Bug
The curation status of the term. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value.
curation status specification
density plot
A density plot is a report graph which is a graphical representation of data where the tint of a particular pixel corresponds to some kind of function corresponding the the amount of data points relativelly with their distance from the the pixel.
Density plot of SSC-H and FSC-H.
OBI_0000179
density plot
group:Flow Cytometry community
person:Allyson Lister
person:Chris Stoeckert
report
2009-03-16: comment from Darren Natale: I am slightly uneasy with the sentence "Topic of the report is on
something that has completed." Should it be restricted to those things
that are completed? For example, a progress report is (usually) about
something that definitely has *not* been completed, or may include
(only) projections. I think the definition would not suffer if the
whole sentence is deleted.
2009-03-16: this was report of results with definition: A report is a narrative object that is a formal statement of the results of an investigation, or of any matter on which definite information is required, made by some person or body instructed or required to do so.
2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI.
2009-08-10 Alan Ruttenberg: Larry Hunter suggests that this be obsoleted and replaced by 'document'. Alan restored as there are OBI dependencies and this merits further discussion
An information content entity assembled by an author for the purpose of providing information for an audience, and that is meant to provide an accurate account of something that happened.
GROUP: OBI
OBI_0000099
PERSON: Alan Ruttenberg
PERSON: Melanie Courtot
PERSON:Chris Stoeckert
disagreement about where reports go. alan: only some gene lists are reports. Is a report all the content of some document? The example of usage suggests that a report may be part of some article. Term needs clarification
journal article, patent application, grant progress report, case report (not patient record)
report
data format specification
2009-03-16: provenance: term imported from OBI_0000187, which had original definition "A data format specification is a plan which organizes
information. Example: The ISO document specifying what encompasses an
XML document; The instructions in a XSD file"
A data format specification is the information content borne by the document published defining the specification.
Example: The ISO document specifying what encompasses an XML document; The instructions in a XSD file
OBI branch derived
OBI_0000187
PERSON: Alan Ruttenberg
PlanAndPlannedProcess Branch
data format specification
data set
2009/10/23 Alan Ruttenberg. The intention is that this term represent collections of like data. So this isn't for, e.g. the whole contents of a cel file, which includes parameters, metadata etc. This is more like java arrays of a certain rather specific type
A data item that is an aggregate of other data items of the same type that have something in common. Averages and distributions can be determined for data sets.
Intensity values in a CEL file or from multiple CEL files comprise a data set (as opposed to the CEL files themselves).
OBI_0000042
data set
group:OBI
person:Allyson Lister
person:Chris Stoeckert
image
An image is an affine projection to a two dimensional surface, of measurements of some quality of an entity or entities repeated at regular intervals across a spatial range, where the measurements are represented as color and luminosity on the projected on surface.
OBI_0000030
group:OBI
image
person:Alan Ruttenberg
person:Allyson
person:Chris Stoeckert
data about an ontology part
Person:Alan Ruttenberg
data about an ontology part
data about an ontology part is a data item about a part of an ontology, for example a term
plan specification
2/3/2009 Comment from OBI review.
Action specification not well enough specified.
Conditional specification not well enough specified.
Question whether all plan specifications have objective specifications.
Request that IAO either clarify these or change definitions not to use them
2009-03-16: provenance: a term a plan was proposed for OBI (OBI_0000344) , edited by the PlanAndPlannedProcess branch. Original definition was " a plan is a specification of a process that is realized by an actor to achieve the objective specified as part of the plan". It has been subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definitionof this, different, term.
Alan Ruttenberg
Alternative previous definition: a plan is a set of instructions that specify how an objective should be achieved
OBI Plan and Planned Process branch
OBI_0000344
To lose weight, go running daily for at least 30 minutes. To isolate plasma from blood, centrifuge tubes at 1100-1300 rpm for 15 minutes.
a directive information entity that, when concretized, is realized in a process in which the bearer tries to achieve the objectives, in part by taking the actions specified.
plan specification
measurement data item
2/2/2009 is_specified_output of some assay?
A data item that is a recording of the output of an assay.
Examples of measurement data are the recoding of the weight of a mouse as {40,mass,"grams"}, the recording of an observation of the behavior of the mouse {,process,"agitated"}, the recording of the expression level of a gene as measured through the process of microarray experiment {3.4,luminosity,}.
OBI_0000305
group:OBI
measurement datum
measurement data item
person:Chris Stoeckert
setting datum
2/3/2009 Feedback from OBI
This should be a "setting specification". There is a question of whether it is information about a realizable or not.
Pro other specification are about realizables.
Cons sometimes specifies a quality which is not a realizable.
A settings datum is a datum that denotes some configuration of an instrument.
Alan grouped these in placeholder for the moment. Name by analogy to measurement datum.
setting datum
conclusion textual entity
2009/09/28 Alan Ruttenberg. Fucoidan-use-case
2009/10/23 Alan Ruttenberg: We need to work on the definition still
A textual entity that expresses the results of reasoning about a problem, for instance as typically found towards the end of scientific papers.
Person:Alan Ruttenberg
conclusion textual entity
that fucoidan has a small statistically significant effect on AT3 level but no useful clinical effect as in-vivo anticoagulant, a paraphrase of part of the last paragraph of the discussion section of the paper 'Pilot clinical study to evaluate the anticoagulant activity of fucoidan', by Lowenthal et. al.PMID:19696660
material information bearer
A material entity in which a concretization of an information content entity inheres.
A page of a paperback novel with writing on it. The paper itself is a material information bearer, the pattern of ink is the information carrier. Additional examples: a hard drive, a brain.
GROUP: IAO
material information bearer
histogram
A histogram is a report graph which is a statistical description of a
distribution in terms of occurrence frequencies of different event classes.
GROUP:OBI
PERSON:Chris Stoeckert
PERSON:James Malone
PERSON:Melanie Courtot
histogram
heatmap
A heatmap is a report graph which is a graphical representation of data
where the values taken by a variable(s) are shown as colors in a
two-dimensional map.
GROUP:OBI
PERSON:Chris Stoeckert
PERSON:James Malone
PERSON:Melanie Courtot
heatmap
dendrogram
A dendrogram is a report graph which is a tree diagram
frequently used to illustrate the arrangement of the clusters produced by a
clustering algorithm.
Dendrograms are often used in computational biology to
illustrate the clustering of genes.
PERSON:Chris Stoeckert
PERSON:James Malone
PERSON:Melanie Courtot
WEB: http://en.wikipedia.org/wiki/Dendrogram
dendrogram
scatter plot
A scatterplot is a graph which uses Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis.
Comparison of gene expression values in two samples can be displayed in a scatter plot
PERSON:Chris Stoeckert
PERSON:James Malone
PERSON:Melanie Courtot
WEB: http://en.wikipedia.org/wiki/Scatterplot
scatter plot
scattergraph
obsolescence reason specification
PERSON: Alan Ruttenberg
PERSON: Melanie Courtot
The creation of this class has been inspired in part by Werner Ceusters' paper, Applying evolutionary terminology auditing to the Gene Ontology.
The reason for which a term has been deprecated. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value.
obsolescence reason specification
textual entity
A textual entity is a part of a manifestation (FRBR sense), a generically dependent continuant whose concretizations are patterns of glyphs intended to be interpreted as words, formulas, etc.
AR, (IAO call 2009-09-01): a document as a whole is not typically a textual entity, because it has pictures in it - rather there are parts of it that are textual entities. Examples: The title, paragraph 2 sentence 7, etc.
MC, 2009-09-14 (following IAO call 2009-09-01): textual entities live at the FRBR (http://en.wikipedia.org/wiki/Functional_Requirements_for_Bibliographic_Records) manifestation level. Everything is significant: line break, pdf and html versions of same document are different textual entities.
PERSON: Lawrence Hunter
Words, sentences, paragraphs, and the written (non-figure) parts of publications are all textual entities
text
textual entity
table
A textual entity that contains a two-dimensional arrangement of texts repeated at regular intervals across a spatial range, such that the spatial relationships among the constituent texts expresses propositions
PERSON: Lawrence Hunter
table
| T F
--+-----
T | T F
F | F F
figure
An information content entity consisting of a two dimensional arrangement of information content entities such that the arrangement itself is about something.
Any picture, diagram or table
PERSON: Lawrence Hunter
figure
diagram
A figure that expresses one or more propositions
A molecular structure ribbon cartoon showing helices, turns and sheets and their relations to each other in space.
PERSON: Lawrence Hunter
diagram
document
A collection of information content entities intended to be understood together as a whole
A journal article, patent application, laboratory notebook, or a book
PERSON: Lawrence Hunter
document
cartesian spatial coordinate datum
1
2009-08-18 Alan Ruttenberg - question to BFO list about whether the BFO sense of the lower dimensional regions is that they are always part of actual space (the three dimensional sort) http://groups.google.com/group/bfo-discuss/browse_thread/thread/9d04e717e39fb617
A cartesian spatial coordinate datum is a representation of a point in a spatial region, in which equal changes in the magnitude of a coordinate value denote length qualities with the same magnitude
Alan Ruttenberg
cartesian spatial coordinate datum
http://groups.google.com/group/bfo-discuss/browse_thread/thread/9d04e717e39fb617
one dimensional cartesian spatial coordinate datum
1
A cartesion spatial coordinate datum that uses one value to specify a position along a one dimensional spatial region
Alan Ruttenberg
one dimensional cartesian spatial coordinate datum
two dimensional cartesian spatial coordinate datum
1
1
A cartesion spatial coordinate datum that uses two values to specify a position within a two dimensional spatial region
Alan Ruttenberg
two dimensional cartesian spatial coordinate datum
three dimensional cartesian spatial coordinate datum
1
1
1
A cartesion spatial coordinate datum that uses three values to specify a position within a three dimensional spatial region
Alan Ruttenberg
three dimensional cartesian spatial coordinate datum
length measurement datum
A scalar measurement datum that is the result of measurement of length quality
Alan Ruttenberg
length measurement datum
denotator type
A denotator type indicates how a term should be interpreted from an ontological perspective.
Alan Ruttenberg
Barry Smith, Werner Ceusters
The Basic Formal Ontology ontology makes a distinction between Universals and defined classes, where the formal are "natural kinds" and the latter arbitrary collections of entities.
denotator type
mass measurement datum
2009/09/28 Alan Ruttenberg. Fucoidan-use-case
A scalar measurement datum that is the result of measurement of mass quality
Person:Alan Ruttenberg
mass measurement datum
time measurement datum
2009/09/28 Alan Ruttenberg. Fucoidan-use-case
A scalar measurement datum that is the result of measuring a temporal interval
Person:Alan Ruttenberg
time measurement datum
documenting
6/11/9: Edited at OBI workshop. We need to be able identify a child form of information artifact which corresponds to something enduring (not brain like). This used to be restricted to physical document or digital entity as the output, but that excludes e.g. an audio cassette tape
Bjoern Peters
Recording the current temperature in a laboratory notebook. Writing a journal article. Updating a patient record in a database. Copying the readout from an instrument into a spreadsheet.
a planned process in which input information is used to create or add to a report
documenting
wikipedia http://en.wikipedia.org/wiki/Documenting
line graph
A line graph is a type of graph created by connecting a series of data
points together with a line.
GROUP:OBI
PERSON:Chris Stoeckert
PERSON:Melanie Courtot
WEB: http://en.wikipedia.org/wiki/Line_chart
line chart
line graph
CRID registry
A data set that consists of CRIDs (centrally registered identifier) and additional information about their corresponding entities, that were recorded in the dataset through an assigning a centrally registered identifier process.
centrally registered identifier registry
CRID registry
IAO call, 20101124: PubMed registry is an instance of CRID registry
PubMed and GenBank both have CRID registries as parts of their database systems.
Original proposal from Bjoern, discussions at IAO calls
PERSON: Alan Ruttenberg
PERSON: Bill Hogan
PERSON: Bjoern Peters
PERSON: Melanie Courtot
time stamped measurement datum
time stamped measurement datum
time sampled measurement data set
A data set that is an aggregate of data recording some measurement at a number of time points. The time series data set is an ordered list of pairs of time measurement data and the corresponding measurement data acquired at that time.
Alan Ruttenberg
experimental time series
pmid:20604925 - time-lapse live cell microscopy
time sampled measurement data set
Viruses
Viruses
Bacteria
Bacteria
eubacteria
Archaea
Archaea
Eukaryota
Eukaryota
eucaryotes
eukaryotes
statistical data analysis
a data transformation that has input of mulitple data and report overall trend of the data.
Jie Zheng, Oliver He
data collection
Jie Zheng, Oliver He
a planned process that gathers and measurs information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes. Data collection results in a collection of data.
WEB: http://en.wikipedia.org/wiki/Data_collection
F distribution
Yongqun He
A continuous probability distribution that is associated with the f statistic.
WEB: http://stattrek.com/probability-distributions/f-distribution.aspx
Fisher-Snedecor distribution
gamma distribution
Yongqun He
A continuous probability distribution that is a two-parameter family of continuous probability distributions.
WEB: http://en.wikipedia.org/wiki/Gamma_distribution
normal distribution
Yongqun He
WEB: http://en.wikipedia.org/wiki/Normal_distribution
A continuous probability distribution that has a symmetrical curve, whose position and shape is determined by its location and scale parameters, the mean and standard deviation respectively.
Gaussian distribution
Student's t distribution
Yongqun He
A continuous probability distribution that is is used to estimate population parameters when the sample size is small and/or when the population variance is unknown.
WEB: http://stattrek.com/probability-distributions/t-distribution.aspx
t-distribution
bivariate normality
WEB: SAS users guide
Marcy Harris
a continuous probability distribution of two varialbes that has the tradtional bell shpe; the distribution of one variable is normal each and every alue of the other variable
log-normal distribution
log normal, lognormal
Marcy Harris
a continuous probability that is the distribution of a random variable X if ln(X) is normally distributed
WEB: http://www.statistics.com
point biserial correlation
A special case of the Pearson product-moment correlation; calculated when either the independent variable or dependent variable is dichotomous while the other variable is non-dichotomous
Marcy Harris
probability distribution
Yongqun He, Jie Zheng
an information content entity that refers to a distribution of a random variable that can be described using a mathematical formula.
WEB: http://en.wikipedia.org/wiki/Probability_distribution
measurement scale
WEB: http://en.wikipedia.org/wiki/Level_of_measurement
level of measurement
an information content entity that represents a type of scale on which a variable is measured, including nominal, ordinal, interval, ratio.
scale of measure
Marcy Harris
outlier
Marcy Harris, Yongqun He
a data item that is numerically distant from the rest of the data; often indicative either measurement error or that the population has a high kurtosis
WEB: http://en.wikipedia.org/wiki/Outlier
test statistic
a data item that is a function of the samples and considered as a numberical summary of a data-set that reduces the data to one value that can be used to perform a hypothesis test. It can be used to test a finding for statistical signifiance
Marcy Harris, Yongqun He
WEB: http://en.wikipedia.org/wiki/Test_statistic
weighted data
Marcy Harris
WEB: SAS users guide
weights are applied when one wants to adjust the impact of cases in the analysis
central tendency
Marcy Harris, Yongqun He
a data item that represents a typical value of a set of values. This term relates to the way in which quantitative data tend to cluster around some value
WEB: http://en.wikipedia.org/wiki/Central_tendency
mode
WEB: http://en.wikipedia.org/wiki/Mode_%28statistics%29
Marcy Harris
a data item that is the value that appears most frequent in a set of data. In a normal distribution the numerical value of the mode is the same as that of the mean and median
cohen's kappa measurement
a statistical measure of agreement for categorical data; a measure of inter-rater agreement or inter-annotator agreement
Marcy Harris
inter-rater agreement, inter-annotator agreement
WEB: http://en.wikipedia.org/wiki/Cohen%27s_kappa
causal model
WEB: http://en.wikipedia.org/wiki/Causal_model
Marcy Harris
an abstract, quantitative model of the causal dependencies and other interrelationships among observed or hypothetical models; an ordered triple , where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U and V.
correlation statistical analysis
WEB: http://www.statistics.com
a meaure of the linear association between two variables that are measured on ordinal, interval or ratio scales
Marcy Harris
hierarchical linear model
multi-level model
Marcy Harris
Mendelian randomization
Yongqun He
multilevel model
hierarchical models
statistical models of parameters that vary at more than one level; a type of regression model that explicitly takes into account structured/nested data
Marcy Harris SAS social science
multivariate analysis
Yongqun He
a data transformation that has more than one independent variable
power calculation
a data transformation that is used to calculate the power of a statistical analysis.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
univariate analysis
a data transformation that has only one independent variable
Yongqun He
statistical association
Marcy Harris
WEB: http://en.wikipedia.org/wiki/Association_%28statistics%29
any relationship between two measured quantities that renders them statistically dependent
cochran-armitage test
Marcy Harris
WEB: http://en.wikipedia.org/wiki/Cochran%E2%80%93Armitage_test_for_trend
a test used in categorical data analysis when the aim is to assess for the presence of an association between a variable with two categories and a variable with k categories
collapsing
Marcy Harris, Yongqun He
bracketing, grouping
a data transformation that combines categories or ranges of values to produce a smaller number of categories
WEB: SAS users guide
covariation
Marcy Harris
WEB: http://en.wikipedia.org/wiki/Covariation
a measure of the extent to which two variables are associated; the extent to which two random variables vary together
goodness of fit
WEB: http://en.wikipedia.org/wiki/Goodness_of_fit
Marcy Harris
describes how well a statistical model fits a set of observations; measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question.
kolmogorov-smirnov two sample test
Marcy Harris
WEB: http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test
a nonparametric test for the equality of continuous, one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).
levene's test
WEB: http://en.wikipedia.org/wiki/Levene%27s_test
Marcy Harris
a data transformation that is specifically an inferential statistic to assess the equality of variances in different sample; tests the null hypothesis that the population variances are equal (called homogeneity of variance or homoscedasticity).
loglinear analysis
a technique used for both hypthesis testing and model building to examine the relationship between more than two categorical variables; uses a likelihood ratio statistic that has an approximate chi-square distribution when the sample size is large
WEB: http://en.wikipedia.org/wiki/Loglinear_analysis
Marcy Harris
mcnemar's test
a normal approximation used on nominal data; applied to 2 × 2 contingency tables to determine whether the row and column marginal frequencies are equal ("marginal homogeneity").
WEB: http://en.wikipedia.org/wiki/McNemar%27s_test
Marcy Harris
statistical model
model
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm; http://en.wikipedia.org/wiki/Statistical_model
Marcy Harris, Yongqun He
a data transformation that represents a mathematical relationship which relates changes in a given response to changes in one or more factors. A statistical model is a formalization of relationships between variables in the form of mathematical equations.
partitioning of variance components
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
Partitioning of the overall variation into assignable components
variance components
statistical effect
Marcy Harris, Yongqun He
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
a data transformation that shows how changing the settings of a factor changes the response. The effect of a single factor is also called a main effect.
effect
statistical variable
variable
a directive information entity that specifies a statistical variable whose value may change within the scope of a given problem or set of operations
WEB: http://en.wikipedia.org/wiki/Variable_%28mathematics%29
Yongqun He
confounding variable specification
confounders
Marcy Harris
WEB: http://en.wikipedia.org/wiki/Mediation_%28statistics%29#Mediator_Variable
a variable specification that specifie a variable that may have a causal impact on both the independent variable and dependent variable; ignoring a confounding variable may bias empirical estimates of the causal effect of the independent variable.
covariate specification
WEB: http://www.statistics.com
a variable specification that specifies a variable used in statistical analysis to correct, adjust, or modify the values of a dependent variable; an independent variable not manipulated by the investigator
Marcy Harris
dichotomous variable specification
a variable that has only two categories
Marcy Harris
dichotomous variable
WEB: SAS users guide
dummy variable
Marcy Harris
a statistical variable with only two categories that reflect only part of the information available in a more comprehensive variable
WEB: SAS users guide
intervening variable specification
A varialbe postulated to be a predictor of one or more dependent variables, and simultaneously predicted by one or more independent variables
WEB: SAS Users Guide
Marcy Harris
intervening variable, mediating variable
binomial distribution
WEB: http://en.wikipedia.org/wiki/Binomial_distribution
A discrete probability distribution that has the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. Such a success/failure experiment is also called a Bernoulli experiment or Bernoulli trial.
Yongqun He
Poisson distribution
Yongqun He
WEB: http://en.wikipedia.org/wiki/Poisson_distribution
A discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time and/or space if these events occur with a known average rate and independently of the time since the last event. The Poisson distribution can also be used for the number of events in other specified intervals such as distance, area or volume.
negative likelihood ratio
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
a likelihood ratio that is calculated by dividing 1 minus sensitivity by specificity ((1-sensitivity)/specificity).
positive likelihood ratio
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
a likelihood ratio that is calculated by dividing sensitivity by 1 minus specificity (sensitivity/(1-specificity)).
absolute risk
Yongqun He
WEB: http://medical-dictionary.thefreedictionary.com/absolute+risk
A data item of an observed or calculated probability of occurrence of an event, X, in a population related to exposure to a specific hazard, infection, trauma; the number of persons suffering from a disease when the exposed population is known with certainty.
accuracy
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
a data item that refers to the number of true positives and true negatives divided by the total number of observations.
censored data
censoring
WEB: SAS users guide
occurs when certain values of a measurement or observation are only partially known, not possible to observe
Marcy Harris
statistical measure
Marcy Harris
a measurement datum that represents a number (statistic) whose size indicates the magnitude of some quantity of interest.
statistic
WEB: SAS users guide
http://en.wikipedia.org/wiki/Statistic
A statistic (singular) is a single measure of some attribute of a sample (e.g., its arithmetic mean value). It is calculated by applying a function (statistical algorithm) to the values of the items of the sample, which are known together as a set of data.
Incidence rate
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
incidence
A data item that refers to the number of new events that have occurred in a specific time interval divided by the population at risk at the beginning of the time interval. The result gives the likelihood of developing an event in that time interval.
Yongqun He
likelihood ratio test
a statistical test used to compare the fit of two models, one of which (the null model) is a special case of the other (the alternative model).
Yongqun He
WEB: http://en.wikipedia.org/wiki/Likelihood-ratio_test
odds ratio
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
A data item that refers to the odds that an individual with a specific condition has been exposed to a risk factor divided by the odds that a control has been exposed. The odds ratio is used in case-control studies. The odds ratio provides a reasonable estimate of the relative risk for uncommon conditions.
prevalence rate
Yongqun He
prevalence
A data item that refers to the number of individuals with a given disease at a given point in time divided by the population at risk at that point in time.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
relative risk
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
A data item that equals the incidence in exposed individuals divided by the incidence in unexposed individuals. The relative risk can be calculated from studies in which the proportion of patients exposed and unexposed to a risk is known, such as a cohort study.
reliability
Yongqun He
a data item that refers to the extent to which repeated measurements of a relatively stable phenomenon fall closely to each other.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
sensitivity
WEB: http://en.wikipedia.org/wiki/Sensitivity_and_specificity
Yongqun He
a data item that measures the proportion of actual positives which are correctly identified as such (e.g. the percentage of sick people who are correctly identified as having the condition).
true positive rate, recall
specificity
true negative rate
WEB: http://en.wikipedia.org/wiki/Sensitivity_and_specificity
a data item that refers to the proportion of negatives in a binary classification test which are correctly identified
Yongqun He
validity
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
a data item that refers to the extent to which an observation reflects the "truth" of the phenomenon being measured.
Yongqun He
polynomial regression
WEB: http://en.wikipedia.org/wiki/Polynomial_regression
A special case of multiple linear regression in which the relationship between the independent variable x and the dependent variable y is modelled as an nth order polynomial
Marcy Harris
data sampling design
WEB: http://www.itl.nist.gov/div898/handbook/ppc/section3/ppc33.htm
sampling plan
a plan specification that provides a detailed outline of which measurements will be taken at what times, on which material, in what manner, and by whom. Sampling plans should be designed in such a way that the resulting data will contain a representative sample of the parameters of interest and allow for all questions, as stated in the goals, to be answered.
Marcy Harris
sampling design
random selection
Any method of sampling that uses some form of random selection, that is, one that will ensure that all units in the population have an equal probability or chance of being selected.
WEB: http://srmo.sagepub.com/view/the-sage-dictionary-of-social-research-methods/SAGE.xml
Marcy Harris
period prevalence
a prevalence rate that occurs at a specific period of time
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
point prevalence rate
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
a prevalence rate that occurs at a specific point of time
Yongqun He
continuous probability distribution
Yongqun He
A probability distribution that is associated with continuous variables and has a probability density function.
WEB: http://en.wikipedia.org/wiki/Continuous_probability_distribution#Continuous_probability_distribution
discrete probability distribution
WEB: http://en.wikipedia.org/wiki/Continuous_probability_distribution#Discrete_probability_distribution
Yongqun He
A probability distribution that is associated with discrete variables and is characterized by a probability mass function.
frequency distribution
WEB: http://statistics.com
Marcy Harris
a tabular summary of a set of data showing the number of items in each of several non-overlapping classes or groupings
cohen's kappa coefficient
WEB: http://en.wikipedia.org/wiki/Cohen%27s_kappa
a statistical measure of inter-rater agreement or inter-annotator agreement for qualitative (categorical) items.
confidence interval
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
A quantitative confidence value that refers to an interval give values within which there is a high probability (95 percent by convention) that the true population value can be found. The calculation of a confidence interval considers the standard deviation of the data and the number of observations. Thus, a confidence interval narrows as the number of observations increases, or its variance (dispersion) decreases.
credible interval
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
A quantitative confidence value that refers to
interquartile range
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
A quantitative confidence value that refers to the upper and lower values defining the central 50 percent of observations. The boundaries are equal to the 25th and 75th percentiles. The interquartile range can be depicted in a box and whiskers plot.
Yongqun He
percentile
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
A quantitative confidence value that equals the percentage of a distribution that is below a specific value. As an example, a child is in 90th percentile for weight if only 10 percent of children the same age weigh more than she does.
power
A quantitative confidence value that refers to the ability of a study to detect a true difference. Negative findings may reflect that the study was underpowered to detect a difference.
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
random error
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
A component of experimental error that occurs due to natural variation in the process.
Marcy Harris
range
Yongqun He
A quantitative confidence value that equals the difference between the largest and smallest observation.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
standard deviation
Yongqun He
A quantitative confidence value that measures the variability of data around the mean.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
type 1 error rate
alpha error
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
A quantitative confidence value that refers to the probability of incorrectly concluding that there is a statistically significant difference in a dataset. Alpha is the number after a p-value. Thus, a statistically significant difference reported as p<0.05 means that there is less than a 5 percent chance that the difference could have occurred by chance.
Yongqun He
type 2 error rate
beta error
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
A quantitative confidence value that refers to the probability of incorrectly concluding that there was no statistically significant difference in a dataset. This error often reflects insufficient power of the study.
bias
Marcy Harris
a quantitative confidence value that is a general statistical term meaning a systematic (not random) deviation from the true value
WEB: http://www.statistics.com
coefficient of variation
WEB: http://www.statistics.com
Marcy Harris, Yongqun He
A quantitative confidence value that is the standard deviation of a data set divided by the mean of the same data set; a normalized measure of dispersion of a probability distribution
variation coefficient
statistical error
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
error
Marcy Harris, Yongqun He
a quantitative confidence value that represents unexplained variation in a collection of observations; comopnents of error include random error and lack of fit error
expected value
Marcy Harris
A quantitative confidence value that represents theoretical average value of a statistic over an infinite number of samples from the same population; the weights correspond to the probabilities in the case of a discrete random variable or densities in the case of a continuous random variable.
WEB: http://en.wikipedia.org/wiki/Expected_value
intraclass correlation coefficient
ICC
WEB: http://en.wikipedia.org/wiki/Intraclass_correlation
a quantitative confidence value that is a descriptive statistic and can be used to describe how strongly units in the same group resemble each other; unlike other correlation measures it operates on data structured as groups, rather than data structured as paired observations.
Marcy Harris, Yongqun He
standardized coefficient
Marcy Harris
WEB: SAS users guide
a quantitative confidence value that has been standardized so that they have variances of 1.0; produces standardized regression coefficients (betas)
logit regression
a type of regression analysis used for predicting the outcome of a categorical dependent variable
logistic regression
WEB: http://en.wikipedia.org/wiki/Logistic_regression
Marcy Harris
nonlinear regression
Marcy Harris
a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables
WEB: http://en.wikipedia.org/wiki/Nonlinear_regression
non-randomization sampling design
non-randomization sampling plan
a data sampling design that does not use randomization for sample selection
Marcy Harris, Jie Zheng, Yongqun He
randomization sampling design
randomization sampling plan
a data sampling design that uses randomization for sample selection
Marcy Harris, Jie Zheng, Yongqun He
interval scale
Marcy Harris
WEB: SAS Users Guide
A measurement scale consisting of equal-sized units; the distance between any two positions is of known size.
nominal scale
Marcy Harris
http://en.wikipedia.org/wiki/Nominal_scale#Nominal_scale
A measurement scale that placing of data into categories, without any order or structure (see related OBI term of categorical measurement datum).
ordinal scale
WEB: http://en.wikipedia.org/wiki/Nominal_scale#Ordinal_scale
Marcy Harris
A measurement scale that rankings on which data can be sorted however the size or magnitude of differences between any data points in a class is unknown, just that one ranking is greater than the other
ratio scale
WEB: http://en.wikipedia.org/wiki/Nominal_scale#Ratio_scale
A measurement scale that is similar to an interval scale, i.e. a magnitude of a continuous quantity and a unit magnitude of the same kind; the distinguishing feature of a ratio scale is a meaningful zero value that means the absence of whatever is measured.
Marcy Harris
disease test sensitivity
a sensitivity that refers to the number of patients with a positive test who have a disease divided by all patients who have the disease. A test with high sensitivity will not miss many patients who have the disease (i.e., few false negative results).
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
disease test specificity
a specificity that refers to the number of patients who have a negative test and do not have the disease divided by the number of patients who do not have the disease. A test with high specificity will infrequently identify patients as having a disease when they do not (i.e., few false positive results).
Yongqun He
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
fixed effect
Marcy Harris
A statistical effect that is associated with an input variable that has a limited number of levels or in which only a limited number of levels are of interest to the experimenter.
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
interaction effect
Marcy Harris
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
moderation
a statistical effect that represents the role of a variable in an estimated model (most often a regression model) and its effect on the dependent variable. A variable that has an interaction effect will have a different effect on the dependent variable, depending on the level of some third variable.
random effect
Marcy Harris
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
A statistical effect that is associated with input variables chosen at random from a population having a large or infinite number of possible values.
lack of fit error
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
Marcy Harris
A statistical error that occurs when the analysis omits one or more important terms or factors from the model
type I error
WEB: http://en.wikipedia.org/wiki/Type_I_and_type_II_errors
Marcy Harris
the null hypothesis is true but has been rejected; a test result that indicates a given condition has been fulfilled, when it actually has not been fulfilled
false positive
type II error
WEB: http://en.wikipedia.org/wiki/Type_I_and_type_II_errors
false negative
the null hypothesis is false but has been accepted; a test result indicates that a condition failed, while it actually was successful.
Marcy Harris
F test
any statistical test in which the test statistic has an F-distribution under the null hypothesis
Marcy Harris
WEB: http://en.wikipedia.org/wiki/F_test
mann-whitney U test
Marcy Harris
Wilcoxon rank-sum test
WEB: http://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U
a non-parametric test of the null hypothesis that two populations are the same against an alternative hypothesis
balanced design
WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm
Marcy Harris
An experimental design where all cells (i.e. treatment combinations) have the same number of observation
case-control study design
a study design that starts with the outcome of interest and works backward to the exposure. For instance, patients with a disease are identified and compared with controls for exposure to a risk factor.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
cohort study design
a study design that starts with an exposure and moves forward to the outcome of interest, even if the data are collected retrospectively. As an example, a group of patients who have variable exposure to a risk factor of interest can be followed over time for an outcome.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
randomized controlled trial design
a study design in which patients are randomly assigned to two or more interventions.
WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms
Yongqun He
complex sample design
A data sampling design that uses something other than simple random selection
Marcy Harris
WEB: SAS users guide
kappa statistic
a generic term for several similar measures of agreement used with categorical data; typically used in assessing the degree to which two or more raters, examining the same data, agree on assigning data to categories
Marcy Harris
WEB: http://www.statistics.com
bartlett's test
WEB: http://en.wikipedia.org/wiki/Bartlett%27s_test
Marcy Harris
a statistial test of whether k samples are from populations with equal variances.
mediating variable
a statistical variable that specifies a variable describing how, rather than when, effects will occur by accounting for the relationship between the independent and dependent variables. A mediating relationship is one in which the path relating A to C is mediated by a third variable (B).
mediating variable, mediation
WEB: http://en.wikipedia.org/wiki/Mediation_%28statistics%29#Mediator_Variable
Marcy Harris, Yongqun He
intervening variable
moderator variable
Marcy Harris
a statistical variable that specifies a variable affecting the direction and/or strength of the relation between dependent and independent variables; occurs when the relationship between two variables depends on a third variable
moderator, interaction
WEB: http://en.wikipedia.org/wiki/Moderator_variable
weighted kappa
Marcy Harris
a weighted data that measures the agreeement for categorical data; a generalization of the Kappa statistics to situations in which the categories are not equal in some respect so weighted by an objective or subjective function
WEB: http://www.statistics.com
median
Marcy Harris
WEB: http://en.wikipedia.org/wiki/Median
the middle value that separates the higher half from the lower half of the data sample, population, or probability distribution
mixed model
WEB: http://en.wikipedia.org/wiki/Mixed_model
a statistical model containing both fixed effects and random effects, that is mixed effects;
Marcy Harris
probability density function
Marcy Harris, Yongqun He
density function
WEB: http://en.wikipedia.org/wiki/Probability_density_function
A data transoformation that represents a mathematical function describing the relative likelihood of a continuous random variable to take on a value
rank order
WEB: http://www.merriam-webster.com/dictionary/rank%20order
a data item that represents an arrangement according to a rank, i.e., the position of a partiuclar case relative to other cases on a defined scale
Marcy Harris, Yongqun He
likihood ratio
a quantitative confidence value that expresses how many times more likely the data are under one model than the other.
WEB: http://en.wikipedia.org/wiki/Likelihood-ratio_test
Yongqun He
chi-square distribution
WEB: http://en.wikipedia.org/wiki/Chi-square_distribution
Yongqun He
A probability distribution that with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables.
inferential statistical data analysis
Jie Zheng, Oliver He
a statistical data analysis that uses patterns in the sample data to draw inferences about the population represented, accounting for randomness.
significantly statistical data analysis
WEB: http://en.wikipedia.org/wiki/Statistics
inferential statistical data analysis objective
Jie Zheng, Oliver He
a statistical data analysis objective where the aim is to make inference using population sample data.
exponential distribution
Yongqun He
WEB: http://en.wikipedia.org/wiki/Exponential_distribution
A continuous probability distribution that describes the time between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate.
random variable
A statistical variable whose value is subject to variations due to chance (i.e. randomness, in a mathematical sense).
WEB: http://en.wikipedia.org/wiki/Random_variable
Jie Zheng, Yongqun He
data collection objective
an objective specification where the aim is to collect data.
Jie Zheng, Oliver He
data collection from experiment
Jie Zheng, Oliver He
a data collection process that results in a collection of data generated from an experiment(s).
data collection from survey
a data collection by sampling process that results in a collection of data generated from an survey(s).
Jie Zheng, Oliver He
data collection from literature
Jie Zheng, Oliver He
a data collection process that results in a collection of data from the literature.
independent variable
Jie Zheng, Yongqun He
A statistical variable that represents the inputs or causes, or are tested to see if they are the cause in an experiment or a modeling.
WEB: http://en.wikipedia.org/wiki/Dependent_and_independent_variables
data collection by sampling
data sampling
Jie Zheng, Oliver He
a data collection process that results in a collection of data from a sampling process
dependent variable
WEB: http://en.wikipedia.org/wiki/Dependent_and_independent_variables
dependent variable
A statistical variable that represents the output or effect, or is tested to see if it is the effect in an experiment or a modeling.
Jie Zheng, Yongqun He
continuous random variable
Jie Zheng, Yongqun He
A random variable which can take an infinite number of possible values
WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar
discrete random variable
A random variable which may take on only a finite number of distinct values such as 0, 1, 2, 3, 4, ...
Jie Zheng, Yongqun He
WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar
Examples of discrete random variables include the number of children in a family, the Friday night attendance at a cinema, the number of patients in a doctor's surgery, the number of defective light bulbs in a box of ten.
numeric data
Jie Zheng, Yongqun He
A data item which consists of digits as opposed to letters of the alphabet of special characters
WEB: http://www.ask.com/question/what-is-numerical-data
data collection design
Jie Zheng, Yongqun He
a plan specification that provides a detailed outline of how data is collected.
fluorescent reporter intensity
group:OBI
A measurement datum that represents the output of a scanner measuring the intensity value for each fluorescent reporter.
From the DT branch: This term and definition were originally submitted by the community to our branch, but we thought they best fit DENRIE. However we see several issues with this. First of all the name 'probe' might not be used in OBI. Instead we have a 'reporter' role. Also, albeit the term 'probe intensity' is often used in communities such as the microarray one, the name 'probe' is ambiguous (some use it to refer to what's on the array, some use it to refer to what's hybed to the array). Furthermore, this concept could possibly be encompassed by combining different OBI terms, such as the roles of analyte, detector and reporter (you need something hybed to a probe on the array to get an intensity) and maybe a more general term for 'measuring intensities'. We need to find the right balance between what is consistent with OBI and combinations of its terms and what is user-friendly. Finally, note that 'intensity' is already in the OBI .owl file and is also in PATO. Why didn't OBI import it from PATO? This might be a problem.
fluorescent reporter intensity
person:Chris Stoeckert
planned process
'Plan' includes a future direction sense. That can be problematic if plans are changed during their execution. There are however implicit contingencies for protocols that an agent has in his mind that can be considered part of the plan, even if the agent didn't have them in mind before. Therefore, a planned process can diverge from what the agent would have said the plan was before executing it, by adjusting to problems encountered during execution (e.g. choosing another reagent with equivalent properties, if the originally planned one has run out.)
6/11/9: Edited at workshop. Used to include: is initiated by an agent
Bjoern Peters
Injecting mice with a vaccine in order to test its efficacy
We are only considering successfully completed planned processes. A plan may be modified, and details added during execution. For a given planned process, the associated realized plan specification is the one encompassing all changes made during execution. This means that all processes in which an agent acts towards achieving some
objectives is a planned process.
branch derived
A processual entity that realizes a plan which is the concretization of a plan specification.
This class merges the previously separated objective driven process and planned process, as they the separation proved hard to maintain. (1/22/09, branch call)
planned process
biological feature identification objective
Biological_feature_identification_objective is an objective role carried out by the proposition defining the aim of a study designed to examine or characterize a particular biological feature.
Jennifer Fostel
biological feature identification objective
classified data set
PERSON: James Malone
PERSON: Monnie McGee
data set with assigned class labels
A data set that is produced as the output of a class prediction data transformation and consists of a data set with assigned class labels.
classified data set
processed material
Examples include gel matrices, filter paper, parafilm and buffer solutions, mass spectrometer, tissue samples
Is a material entity that is created or changed during material processing.
PERSON: Alan Ruttenberg
processed material
ratio of collected to emitted light
Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt
10%
A measurement datum measuring the amount of light collected s compared to the total amount of emitted light in the detector component of a flow cytometer instrument. The datum has a qualitative role
person:Chris Stoeckert
person:Kevin Clancy
ratio of collected to emitted light
investigation
Could add specific objective specification
Lung cancer investigation using expression profiling, a stem cell transplant investigation, biobanking is not an investigation, though it may be part of an investigation
study
Bjoern Peters
Following OBI call November 2012,26th: it was decided there was no need for adding "achieves objective of drawing conclusion" as existing relations were providing equivalent ability. this note closes the issue and validates the class definition to be part of the OBI core
editor = PRS
OBI branch derived
a planned process that consists of parts: planning, study design execution, documentation and which produce conclusion(s).
investigation
evaluant role
Feb 10, 2009. changes after discussion at OBI Consortium Workshop Feb 2-6, 2009. accepted as core term.
GROUP: Role Branch
OBI
Role call - 17nov-08: JF and MC think an evaluant role is always specified input of a process. Even in the case where we have an assay taking blood as evaluant and outputting blood, the blood is not the specified output at the end of the assay (the concentration of glucose in the blood is)
When a specimen of blood is assayed for glucose concentration, the blood has the evaluant role. When measuring the mass of a mouse, the evaluant is the mouse. When measuring the time of DNA replication, the evaluant is the DNA. When measuring the intensity of light on a surface, the evaluant is the light source.
a role that inheres in a material entity that is realized in an assay in which data is generated about the bearer of the evaluant role
evaluant role
examples of features that could be described in an evaluant: quality.... e.g. "contains 10 pg/ml IL2", or "no glucose detected")
assay
Assay the wavelength of light emitted by excited Neon atoms. Count of geese flying over a house.
any method
study assay
12/3/12: BP: the reference to the 'physical examination' is included to point out that a prediction is not an assay, as that does not require physical examiniation.
A planned process with the objective to produce information about the material entity that is the evaluant, by physically examining it or its proxies.
OBI branch derived
PlanAndPlannedProcess Branch
assay
measuring
scientific observation
quantitative confidence value
group:OBI
A data item which is used to indicate the degree of uncertainty about a measurement.
person:Chris Stoeckert
quantitative confidence value
diagnosis textual entity
Jennifer Fostel
diagnosis is an assessment of a disease or injury, its likely prognosis and treatment.
diagnosis textual entity
material processing
A cell lysis, production of a cloning vector, creating a buffer.
PERSON: Frank Gibson
PERSON: Jennifer Fostel
PERSON: Melanie Courtot
PERSON: Philippe Rocca Serra
A planned process which results in physical changes in a specified input material
OBI branch derived
PERSON: Bjoern Peters
material processing
material transformation
measured expression level
OBI Data Transformation branch
A measurement datum that is the outcome of the quantification of an assay for the activity of a gene, or the number of RNA transcripts.
Examples are quantified data from an expression microarray experiment, PCR measurements, etc.
measured expression level
person:Chris Stoeckert
specimen role
22Jun09. The definition includes whole organisms, and can include a human. The link between specimen role and study subject role has been removed. A specimen taken as part of a case study is not considered to be a population representative, while a specimen taken as representing a population, e.g. person taken from a cohort, blood specimen taken from an animal) would be considered a population representative and would also bear material sample role.
GROUP: Role Branch
Note: definition is in specimen creation objective which is defined as an objective to obtain and store a material entity for potential use as an input during an investigation.
OBI
liver section; a portion of a culture of cells; a nemotode or other animal once no longer a subject (generally killed); portion of blood from a patient.
a role borne by a material entity that is gained during a specimen collection process and that can be realized by use of the specimen in an investigation
blood taken from animal: animal continues in study, whereas blood has role specimen.
something taken from study subject, leaves the study and becomes the specimen.
parasite example
- when parasite in people we study people, people are subjects and parasites are specimen
- when parasite extracted, they become subject in the following study
specimen can later be subject.
specimen role
intervention design
An intervention design is a study design in which a controlled process applied to the subjects (the intervention) serves as the independent variable manipulated by the experimentalist. The treatment (perturbation or intervention) defined can be defined as a combination of values taken by independent variable manipulated by the experimentalists are applied to the recruited subjects assigned (possibly by applying specific methods) to treatment groups. The specificity of intervention design is the fact that independent variables are being manipulated and a response of the biological system is evaluated via response variables as monitored by possibly a series of assays.
OBI branch derived
PMID: 18208636.Br J Nutr. 2008 Jan 22;:1-11.Effect of vitamin D supplementation on bone and vitamin D status among Pakistani immigrants in Denmark: a randomised double-blinded placebo-controlled intervention study.
Philppe Rocca-Serra
intervention design
gene list
group:OBI
A data set of the names or identifiers of genes that are the outcome of an analysis or have been put together for the purpose of an analysis.
Gene lists may arise from analysis to determine differentially expressed genes, may be collected from the literature for involvement in a particular process or pathway (e.g., inflammation), or may be the input for gene set enrichment analysis.
gene list
kind of report. (alan) need to be careful to distinguish from output of a data transformation or calculation. A gene list is a report when it is published as such? Relates to question of whether report is a whole, or whether it can be a part of some other narrative object.
person:Chris Stoeckert
number of particles in subset
Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt
500, 200, 0
A measurement datum measuring the number of subjects in a defined subset in a flow cytometer instrument. The datum has a qualitative role
number of particles in subset
person:Kevin Clancy
number of lost events electronic
Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt
74, 0, 14 events lost due to data acquisition electronic coincidence.
A measurement datum measuring the number of analysis events lost due to errors in data acquisition electronic coincidence in a flow cytometer instrument. The datum has a qualitative role.
number of lost events electronic
person:Kevin Clancy
parameter threshold
Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt
0.01, 0.03
A measurement datum measuring the minimal signal that must be detected to generate an electrical event, as compared to the maximal detected signal in a flow cytometer instrument. The datum has a qualitative role
parameter threshold
person:Kevin Clancy
p-value
May be outside the scope of OBI long term, is needed so is retained
PMID:19696660
in contrast to the in-vivo data AT-III increased significantly from
113.5% at baseline to 117% after 4 days (n = 10, P-value= 0.02; Table 2).
WEB: http://en.wikipedia.org/wiki/P-value
A quantitative confidence value that represents the probability of obtaining a result at least as extreme as that actually obtained, assuming that the actual value was the result of chance alone.
PERSON:Chris Stoeckert
p-value
methodology testing objective
Jennifer Fostel
Methodology_testing_objective is an objective role carried out by a proposition defining the aim of the study is to examine the effect of using different methodologies.
methodology testing objective
standard error
group:OBI
A quantitative confidence value which is the standard deviations of the sample in a frequency distribution, obtained by dividing the standard deviation by the total number of cases in the frequency distribution.
person:Chris Stoeckert
see P-Value
standard error
software testing objective
Jennifer Fostel
Software_testing_objective is a hardware_optimization role describing a study designed to examine the effects of using different software or software parameters, e.g. data processing software.
software testing objective
organization
GROUP: OBI
PERSON: Alan Ruttenberg
PERSON: Bjoern Peters
PERSON: Philippe Rocca-Serra
PERSON: Susanna Sansone
An entity that can bear roles, has members, and has a set of organization rules. Members of organizations are either organizations themselves or individual people. Members can bear specific organization member roles that are determined in the organization rules. The organization rules also determine how decisions are made on behalf of the organization by the organization members.
BP: The definition summarizes long email discussions on the OBI developer, roles, biomaterial and denrie branches. It leaves open if an organization is a material entity or a dependent continuant, as no consensus was reached on that. The current placement as material is therefore temporary, in order to move forward with development. Here is the entire email summary, on which the definition is based:
1) there are organization_member_roles (president, treasurer, branch
editor), with individual persons as bearers
2) there are organization_roles (employer, owner, vendor, patent holder)
3) an organization has a charter / rules / bylaws, which specify what roles
there are, how they should be realized, and how to modify the
charter/rules/bylaws themselves.
It is debatable what the organization itself is (some kind of dependent
continuant or an aggregate of people). This also determines who/what the
bearer of organization_roles' are. My personal favorite is still to define
organization as a kind of 'legal entity', but thinking it through leads to
all kinds of questions that are clearly outside the scope of OBI.
Interestingly enough, it does not seem to matter much where we place
organization itself, as long as we can subclass it (University, Corporation,
Government Agency, Hospital), instantiate it (Affymetrix, NCBI, NIH, ISO,
W3C, University of Oklahoma), and have it play roles.
This leads to my proposal: We define organization through the statements 1 -
3 above, but without an 'is a' statement for now. We can leave it in its
current place in the is_a hierarchy (material entity) or move it up to
'continuant'. We leave further clarifications to BFO, and close this issue
for now.
PMID: 16353909.AAPS J. 2005 Sep 22;7(2):E274-80. Review. The joint food and agriculture organization of the United Nations/World Health Organization Expert Committee on Food Additives and its role in the evaluation of the safety of veterinary drug residues in foods.
organization
cluster
group:OBI
A data set which is a subset of data that are a similar to each other in some way.
Cluster of the lymphocytes population.
cluster
person:Allyson
person:Chris Stoeckert
organism feature identification objective
Jennifer Fostel
Organism_feature_identification_objective is a biological_feature_identification_objective role describing a study designed to examine or characterize a biological feature monitored at the level of the organism, e.g. height, weight, stage of development, stage of life cycle.
organism feature identification objective
number of lost events computer
Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt
0, 125, 787 events lost due to computer busy.
A measurement datum recording the number of measurement events lost due to overloading of the analysis chip in a flow cytometer instrument. The datum has a qualitative role
number of lost events computer
person:Kevin Clancy
protocol
study protocol
A plan specification which has sufficient level of detail and quantitative information to communicate it between investigation agents, so that different investigation agents will reliably be able to independently reproduce the process.
OBI branch derived + wikipedia (http://en.wikipedia.org/wiki/Protocol_%28natural_sciences%29)
PCR protocol, has objective specification, amplify DNA fragment of interest, and has action specification describes the amounts of experimental reagents used (e..g. buffers, dNTPS, enzyme), and the temperature and cycle time settings for running the PCR.
PlanAndPlannedProcess Branch
protocol
adding a material entity into a target
BP
Class was renamed from 'administering substance', as this is commonly used only for additions into organisms.
Injecting a drug into a mouse. Adding IL-2 to a cell culture. Adding NaCl into water.
branch derived
adding a material entity into a target
is a process with the objective to place a material entity bearing the 'material to be added role' into a material bearing the 'target of material addition role'.
material to be added role
9 March 09 from discussion with PA branch
OBI
Role Branch
drug added to a buffer contained in a tube; substance injected into an animal;
material to be added role
material to be added role is a protocol participant role realized by a material which is added into a material bearing the target of material addition role in a material addition process
drawing a conclusion based on data
Bjoern Peters
Concluding that a gene is upregulated in a tissue sample based on the band intensity in a western blot. Concluding that a patient has a infection based on measurement of an elevated body temperature and reported headache. Concluding that there were problems in an investigation because data from PCR and microarray are conflicting. Concluding that 'defects in gene XYZ cause cancer due to improper DNA repair' based on data from experiments in that study that gene XYZ is involved in DNA repair, and the conclusion of a previous study that cancer patients have an increased number of mutations in this gene.
PERSON: Bjoern Peters
PERSON: Jennifer Fostel
A planned process in which data gathered in an investigation is evaluated in the context of existing knowledge with the objective to generate more general conclusions or to conclude that the data does not allow one to draw general conclusion
drawing a conclusion based on data
planning
7/18/2011 BP: planning used to itself be a planned process. Barry Smith pointed out that this would lead to an infinite regression, as there would have to be a plan to conduct a planning process, which in itself would be the result of planning etc. Therefore, the restrictions on 'planning' were loosened to allow for informal processes that result in an 'ad hoc plan '. This required changing from 'has_specified_output some plan specifiction' to 'has_participant some plan specification'.
Bjoern Peters
Bjoern Peters
Plans and Planned Processes Branch
The process of a scientist thinking about and deciding what reagents to use as part of a protocol for an experiment. Note that the scientist could be human or a "robot scientist" executing software.
a process of creating or modifying a plan specification
planning
inductive reasoning
Bjoern Peters
wikipedia: http://en.wikipedia.org/wiki/Inductive_reasoning
BP: 10/22/122: After changing the parent class to drawing a conclusion *based on data* it is no longer clear that this class is needed; minimally it needs a better definition to distinguish it.
Proposal is to obsolete.
Based on the observation that all lung cancer patients treated with aspirin in our clinical trial survived longer than the control group, we conclude by inductive reasining that aspirin has a therapeutic effect on lung cancer.
a interpreting data that is used to ascribe properties or relations to types based on an observation instance (i.e., on a number of observations or experiences); or to formulate laws based on limited observations of recurring phenomenal patterns.
inductive reasoning
hypothesis driven investigation
OBI branch derived
PlanAndPlannedProcess Branch
hypothesis driven investigation
is an investigation with the goal to test one or more hypothesis
hypothesis generating investigation
OBI branch derived
PlanAndPlannedProcess Branch
hypothesis generating investigation
is an investigation in which data is generated and analyzed with the purpose of generating new hypothesis
averaging objective
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
A mean calculation which has averaging objective is a descriptive statistics calculation in which the mean is calculated by taking the sum of all of the observations in a data set divided by the total number of observations. It gives a measure of the 'center of gravity' for the data set. It is also known as the first moment.
An averaging objective is a data transformation objective where the aim is to perform mean calculations on the input of the data transformation.
James Malone
averaging objective
adding material objective
BP
creating a mouse infected with LCM virus
adding material objective
is the specification of an objective to add a material into a target material. The adding is asymmetric in the sense that the target material largely retains its identity
assay objective
PPPB branch
PPPB branch
the objective to determine the weight of a mouse.
an objective specification to determine a specified type of information about an evaluated entity (the material entity bearing evaluant role)
assay objective
target of material addition role
From Branch discussion with BP, AR, MC -- there is a need for the recipient to interact with the administered material. for example, a tooth receiving a filling was not considered to be a target role.
GROUP: Role Branch
OBI
peritoneum of an animal receiving an interperitoneal injection; solution in a tube receiving additional material; location of absorbed material following a dermal application.
target of material addition role is a role realized by an entity into which a material is added in a material addition process
target of material addition role
normalized data set
PERSON: James Malone
PERSON: Melanie Courtot
A data set that is produced as the output of a normalization data transformation.
normalized data set
material transformation objective
GROUP: OBI PlanAndPlannedProcess Branch
PERSON: Bjoern Peters
PERSON: Frank Gibson
PERSON: Jennifer Fostel
PERSON: Melanie Courtot
PERSON: Philippe Rocca-Serra
The objective to create a mouse infected with LCM virus. The objective to create a defined solution of PBS.
an objective specifiction that creates an specific output object from input materials.
artifact creation objective
material transformation objective
study design execution
6/11/9: edited at workshop. Used to be: study design execution is a process with the objective to generate data according to a concretized study design. The execution of a study design is part of an investigation, and minimally consists of an assay or data transformation.
a planned process that realizes the concretization of a study design
branch derived
injecting a mouse with PBS solution, weighing it, and recording the weight according to a study design.
removed axiom has_part some (assay or 'data transformation') per discussion on protocol application mailing list to improve reasoner performance. The axiom is still desired.
study design execution
clustered data set
A clustered data set is the output of a K means clustering data transformation
AR thinks could be a data item instead
PERSON: James Malone
PERSON: Monnie McGee
data set with assigned discovered class labels
A data set that is produced as the output of a class discovery data transformation and consists of a data set with assigned discovered class labels.
clustered data set
differential expression analysis data transformation
A differential expression analysis data transformation is a data transformation that has objective differential expression analysis and that consists of
James Malone
Melanie Courtot
Monnie McGee
WEB:
differential expression analysis data transformation
material combination
Mixing two fluids. Adding salt into water. Injecting a mouse with PBS.
bp
bp
created at workshop as parent class for 'adding material into target', which is asymmetric, while combination encompasses all addition processes.
is a material processing with the objective to combine two or more material entities as input into a single material entity as output.
material combination
fuzzy clustering objective
PERSON: James Malone
PERSON: Ryan Brinkman
A fuzzy clustering objective is a data transformation objective where the aim is to assign input objects (typically vectors of attributes) a probability that a point belongs to a class, where the number of class and their specifications are not known a priori.
James Malone
fuzzy clustering objective
data set of predicted values according to fitted curve
PERSON: James Malone
PERSON: Monnie McGee
A data set which is the output of a curve fitting data transformation in which the aim is to find a curve which matches a series of data points and possibly other constraints.
data set of predicted values according to fitted curve
data representational model
2009-02-28: work on this term has been finalized during the OBI workshop winter 2009
Data representational model is an information content entity of the relationships between data items. A data representational model is encoded in a data format specification such as for cytoscape or biopax.
GROUP: OBI
Melanie Courtot
data representational model
data structure
data structure specification
gene regulatory graph model
phylogenetic tree
protein interaction network
specimen collection
5/31/2012: This process is not necessarily an acquisition, as specimens may be collected from materials already in posession
6/9/09: used at workshop
A planned process with the objective of collecting a specimen.
Bjoern Peters
Note: definition is in specimen creation objective which is defined as an objective to obtain and store a material entity for potential use as an input during an investigation.
specimen collection
drawing blood from a patient for analysis, collecting a piece of a plant for depositing in a herbarium, buying meat from a butcher in order to measure its protein content in an investigation
Philly2013: A specimen collection can have as part a material entity acquisition, such as ordering from a bank. The distinction is that specimen collection necessarily involves the creation of a specimen role. However ordering cell lines cells from ATCC for use in an investigation is NOT a specimen collection, because the cell lines already have a specimen role.
Philly2013: The specimen_role for the specimen is created during the specimen collection process.
background corrected data set
PERSON: James Malone
PERSON: Melanie Courtot
A data set that is produced as the output of a background correction data transformation.
background corrected data set
error corrected data set
PERSON: James Malone
PERSON: Monnie McGee
A data set that is produced as the output of an error correction data transformation and consists of producing a data set which has had erroneous contributions from the input to the data transformation removed (corrected for).
error corrected data set
class prediction data transformation
James Malone
supervised classification data transformation
A class prediction data transformation (sometimes called supervised classification) is a data transformation that has objective class prediction.
PERSON: James Malone
class prediction data transformation
background correction data transformation
James Malone
A background correction data transformation (sometimes called supervised classification) is a data transformation that has the objective background correction.
PERSON: James Malone
background correction data transformation
error correction data transformation
EDITORS
Monnie McGee
An error correction data transformation is a data transformation that has the objective of error correction, where the aim is to remove (correct for) erroneous contributions from the input to the data transformation.
James Malone
error correction data transformation
statistical hypothesis test
James Malone
A statistical hypothesis test data transformation is a data transformation that has objective statistical hypothesis test.
PERSON: James Malone
statistical hypothesis test
center value
PERSON: James Malone
PERSON: Monnie McGee
median
A data item that is produced as the output of a center calculation data transformation and represents the center value of the input data.
center value
statistical hypothesis test objective
Person:Helen Parkinson
WEB: http://en.wikipedia.org/wiki/Statistical_hypothesis_testing
hypothesis test objective
is a data transformation objective where the aim is to estimate statistical significance with the aim of proving or disproving a hypothesis by means of some data transformation
James Malone
statistical hypothesis test objective
reduced dimension data set
PERSON: James Malone
PERSON: Monnie McGee
A data set that is produced as the output of a data vector reduction data transformation and consists of producing a data set which has fewer vectors than the input data set.
reduced dimension data set
average value
PERSON: James Malone
PERSON: Monnie McGee
arithmetic mean
A data item that is produced as the output of an averaging data transformation and represents the average value of the input data.
average value
specimen collection objective
A objective specification to obtain a material entity for potential use as an input during an investigation.
Bjoern Peters
Bjoern Peters
The objective to collect bits of excrement in the rainforest. The objective to obtain a blood sample from a patient.
specimen collection objective
material combination objective
PPPB branch
bp
is an objective to obtain an output material that contains several input materials.
material combination objective
support vector machine
A support vector machine is a data transformation with a class prediction objective based on the construction of a separating hyperplane that maximizes the margin between two data sets of vectors in n-dimensional space.
James Malone
PERSON: Ryan Brinkman
Ryan Brinkman
SVM
support vector machine
self-organizing map
A self-organizing map (SOM) is an artificial neural network with objective class discovery that uses a neighborhood function to preserve the topological properties of a dataset to produce low-dimensional (typically 2) discretized representation of the training data set. A set of artificial neurons learn to map points in an input space to coordinates in an output space. The input space can have different dimensions and topology from the output space, and the SOM will attempt to preserve these.
James Malone
PERSON: Ryan Brinkman
Ryan Brinkman
SOM
self-organizing map
decision tree induction objective
A decision tree induction objective is a data transformation objective in which a tree-like graph of edges and nodes is created and from which the selection of each branch requires that some type of logical decision is made.
James Malone
decision tree induction objective
decision tree building data transformation
James Malone
A decision tree building data transformation is a data transformation that has objective decision tree induction.
PERSON: James Malone
decision tree building data transformation
peak matching
James Malone
PERSON: Ryan Brinkman
Peak matching is a data transformation performed on a dataset of a graph of ordered data points (e.g. a spectrum) with the objective of pattern matching local maxima above a noise threshold
Ryan Brinkman
peak matching
k-nearest neighbors
k-NN
A k-nearest neighbors is a data transformation which achieves a class discovery or partitioning objective, in which an input data object with vector y is assigned to a class label based upon the k closest training data set points to y; where k is the largest value that class label is assigned.
James Malone
PERSON: James Malone
k-nearest neighbors
Student's t-test
James Malone
Studen't t-test is a data transformation with the objective of a statistical hypothesis test in which the test statistic has a Student's t distribution if the null hypothesis is true. It is applied when the population is assumed to be normally distributed but the sample sizes are small enough that the statistic on which inference is based is not normally distributed because it relies on an uncertain estimate of standard deviation rather than on a precisely known value.
Student's t-test
WEB: http://en.wikipedia.org/wiki/T-test
topologically preserved clustered data set
A clustered data set in which the topology, i.e. the spatial properties between data points, is preserved from the original input data from which it was derived.
James Malone
PERSON: James Malone
the output data set generated from a self-organizing map.
topologically preserved clustered data set
CART
classification and regression trees
A CART (classification and regression trees) is a data transformation method for producing a classification or regression model with a tree-based structure.
BOOK: David J. Hand, Heikki Mannila and Padhraic Smyth (2001) Principles of Data Mining.
CART
James Malone
study design independent variable
2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify thisdefinition please notify OBI.
PERSON: Alan Ruttenberg
PERSON: Bjoern Peters
PERSON: Chris Stoeckert
Web: http://en.wikipedia.org/wiki/Dependent_and_independent_variables
study factor
In a study in which gene expression is measured in patients between 8 month to 4 years old that have mild or severe malaria and in which the hypothesis is that gene expression in that age group is a function of disease status, disease status is the independent variable.
2/2/2009 Original definition - In the design of experiments, independent variables are those whose values are controlled or selected by the person experimenting (experimenter) to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled.
independent variable
In the Philly 2013 workshop the label was chosen to distinguish it from "dependent variable" as used in statistical modelling. See: http://en.wikipedia.org/wiki/Statistical_modeling
a directive information entity that is part of a study design. Independent variables are entities whose values are selected to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled
experimental factor
study design independent variable
study design dependent variable
2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify thisdefinition please notify OBI.
PERSON: Alan Ruttenberg
PERSON: Bjoern Peters
PERSON: Chris Stoeckert
WEB: http://en.wikipedia.org/wiki/Dependent_and_independent_variables
In a study in which gene expression is measured in patients between 8 month to 4 years old that have mild or severe malaria and in which the hypothesis is that gene expression in that age group is a function of disease status, the gene expression is the dependent variable.
2/2/2009 In the design of experiments, independent variables are those whose values are controlled or selected by the person experimenting (experimenter) to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled.
In the Philly 2013 workshop the label was chosen to distinguish it from "dependent variable" as used in statistical modelling. See: http://en.wikipedia.org/wiki/Statistical_modeling
dependent variable
dependent variable specification is part of a study design. The dependent variable is the event studied and expected to change when the independent variable varies.
study design dependent variable
survival rate
A measurement data that represents the percentage of people or animals in a study or treatment group who are alive for a given period of time after diagnosis or initiation of monitoring.
Oliver He
adapted from wikipedia
http://en.wikipedia.org/wiki/Survival_rate
survival rate
multiple testing correction objective
A multiple testing correction objectives is a data transformation objective where the aim is to correct for a set of statistical inferences considered simultaneously
Application of the Bonferroni correction
http://en.wikipedia.org/wiki/Multiple_Testing_Correction
multiple comparison correction objective
multiple testing correction objective
statistical model validation
A data transformation which assesses how the results of a statistical analysis will generalize to an independent data set.
Helen Parkinson
Using the expression levels of 20 proteins to predict whether a cancer patient will respond to a drug. A practical goal would be to determine which subset of the 20 features should be used to produce the best predictive model. - wikipedia
http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29
statistical model validation
spike train datum
A measurement datum which represents information about an ordered series of action potentials in an organism's CNS measured over time.
Helen Parkinson, Alan Ruttenberg
Jessica Turner, NIF
Measurement of temporal regularity of spike train responses in auditory nerve fibers of the green treefrog
needs more work to see exactly what the data set looks like - HP
spike train datum
spike train measurement
primary structure of DNA macromolecule
BP et al
a quality of a DNA molecule that inheres in its bearer due to the order of its DNA nucleotide residues.
placeholder for SO
primary structure of DNA macromolecule
Likelihood-ratio test
Likelihood-ratio is a data transformation which tests whether there is evidence of the need to move from a simple model to a more complicated one (where the simple model is nested within the complicated one); tests of the goodness-of-fit between two models.
Likelihood-ratio test
Tina Boussard
pattern matching objective
A pattern matching objective aims to detect the presence of the constituents of a given pattern. In contrast to pattern recognition, the pattern is rigidly specified. Patterns are typicall sequences or trees.
Tina Boussard
http://en.wikipedia.org/wiki/Pattern_matching
pattern matching objective
study intervention
GROUP: OBI
PERSON: Bjoern Peters
study intervention
the part of the execution of an intervention design study which is varied between two or more subjects in the study
categorical measurement datum
A measurement datum that is reported on a categorical scale
Bjoern Peters
Bjoern Peters
categorical measurement datum
nominal mesurement datum
handedness assay
A handedness assay measures the unequal distribution of fine motor skill between the left and right hands typically in human subjects by means of some questionnaire and scoring procedure.
Helen Parkinson
The Edinburgh handedness assay is a specific method of determing handedness
handedness assay
handedness test
http://en.wikipedia.org/wiki/Handedness
compound treatment design
MO_555 compound_treatment_design
PERSON: Bjoern Peters
This is meant to include all kinds of material administrations, including vaccinations, chemical compounds etc.
an intervention design in which the treatment is the administration of a compound
compound treatment design
categorical label
A label that is part of a categorical datum and that indicates the value of the data item on the categorical scale.
Bjoern Peters
Bjoern Peters
The labels 'positive' vs. 'negative', or 'left handed', 'right handed', 'ambidexterous', or 'strongly binding', 'weakly binding' , 'not binding', or '+++', '++', '+', '-' etc. form scales of categorical labels.
categorical label
dose specification
a directive information entity that describes the dose that will be administered to a target
a protocol specifying to administer 1 ml of vaccine to a mouse
dose specification
scalar score from composite inputs
1
questionaire score
scalar score from composite inputs
A measurement datum which is the result of combining multiple datum. For example, a mean or summary score.
JT: We included this because we wanted to talk about an output from a questionnaire that summarized the answers to the questionnaire, but which was not actually the answer to any single question.
JZ: can we defined it logically as the output of some data transformation, like aggragate data transformation?
Person: Jessica Turner
Person: Jessica Turner
sequence data
A measurement datum that representing the primary structure of a macromolecule(it's sequence) sometimes associated with an indicator of confidence of that measurement.
GROUP: OBI
Person:Chris Stoeckert
example of usage: the representation of a nucleotide sequence in FASTA format used for a sequence similarity search.
sequence data
handedness categorical measurement datum
A datum used to record the answer to a self assessment of whether a person uses their left hand, right hand primarily or each hand equally
PERSON:Alan Ruttenberg
PERSON:Jessica Turner
handedness categorical measurement datum
dose
A measurement datum that measures the quantity of something that may be administered to an organism or that an organism may be exposed to. Quantities of nutrients, drugs, vaccines and toxins are referred to as doses.
An organism has been injected 1ml of vaccine
dose
growth condition intervention design
A study design in which the independent variable is the environmental condition in which the specimen is growing
MO_588 growth_condition_design
PERSON: Bjoern Peters
growth condition intervention design
performing a diagnosis
Diagnosing that a patient has pneumonia based on information on measurements of temperature, sound of breathing, and patient complaining about a headache.
The interpretation of the information available about bodily features (clinical picture) of a patient resulting in a diagnosis
performing a diagnosis
Edinburgh score
1
Edinburgh score
PMID:5146491#Oldfield, R.C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9, 97-113
Person: Alan Ruttenberg
Person:Jessica Turner
WEB:http://www.cse.yorku.ca/course_archive/2006-07/W/4441/EdinburghInventory.html
A score that measures the dominance of a person's right or left hand in everyday activities.
administration of material to specimen
Bjoern Peters
Bjoern Peters
Staining cells in a tissue slice with a dye.
The directed combination of a material entity with a specimen.
administration of material to specimen
growth environment
OBI group
PERSON:Richard Scheuermann, Jie Zheng, Bjoern Peters
Right now this may be incomplete. Should also cover e.g. sound, light as well.
The collection of material entities and their qualities that are located near a live organism, tissue or cell and can influence its growth.
growth environment
questionnaire
Need to clarify if this is a document or a directive information entity (or what their connection is))
questionnaire
A document with a set of printed or written questions with a choice of answers, devised for the purposes of a survey or statistical study.
JT: It plays a role in collecting data that could be fleshed out more; but I'm thinking it is, in itself, an edited document.
JZ: based on textual definition of edited document, it can be defined as N&S. I prefer to leave questionnaire as a document now. We can add more restrictions in the future and use that to determine it is an edited document or not.
Merriam-Webster
PERSON: Jessica Turner
Edinburgh handedness assay
Edinburgh handedness assay
PERSON:Jessica Turner
Person:Alan Ruttenberg
The Edinburgh Handedness assay is an assay in which a set of questions = the Edinburgh Handedness inventory - is asked and the answers to these questions are turned into a score, used to assess the dominance of a person's right or left hand in everyday activities. The inventory can be used by an observer assessing the person, or by a person self-reporting hand use. The latter method tends to be less reliable due to a person over-attributing tasks to the dominant hand.
WEB:http://en.wikipedia.org/wiki/Edinburgh_Handedness_Inventory
feature extraction
A planed process with objective of obtaining quantified values from an image.
MO_928: feature_extraction
PERSON: Jie Zheng
feature extraction
binding constant
10/6/11 BP: The distinction between binding datum and binding constant is based on the later being part of an equation. That should be captured in the logical definition here, and used to make it to a defined class.
A binding datum about the disposition of two or more material entities to form complexes which comes in the form of a scalar and unit that are utilized in equations that model the binding process
PERSON: Bjoern Peters, Randi Vita, Jason Greenbaum
The predicted or measured binding affinity of a peptide to a MHC molecule can be captured in the binding constants "IC50 = 12 nM" or "t 1/2 = 30 minutes".
binding constant
genetically modified material
GROUP: OBI
PERSON: Jie Zheng
a material entity, organism or cell, that is the output of a genetic transformation process.
genetically modified material
term is proposed by BP on Oct 25, 2010 dev call
genetic transformation objective
suggested to be added by BP and AR during Oct 25, 2010 dev call
Person: Jie Zheng
Person: Jie Zheng
a material transformation objective aims to create genetically modified organism or cell
genetic transformation objective
3D structural organization datum
3D structural organization datum
A measurement datum that describes the structural orientation of a material entity in 3D space.
PERSON: Jason Greenbaum, Randi Vita, Bjoern Peters
The atom coordinates found in a PDB (Protein Data Bank) file, generated by X Ray crystallography or NMR.
age since planting measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since planting, the process of placing a plant in media (e.g. soil) to allow it to grow, which excludes sowing.
Discussed by Jie and Chris, proposed to combine with different kinds of processes as initial time point. Proposed 'age measurement assay' is proceeded by some process. The process can be any kind of process defined in OBI. Think it is more flexible. However, it is hard to model due to lake of temporal predicates on Nov 15, 2010 dev call.
Term proposed by Bjoern on Nov 8, 2010 dev call
Supported by Alan on Nov 15, 2010 dev call
MO_495 planting
PERSON:Chris Stoeckert, Jie Zheng
age since planting measurement datum
age since hatching measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since hatching, the process of emergence from an egg.
MO_745 hatching
PERSON:Chris Stoeckert, Jie Zheng
age since hatching measurement datum
age measurement assay
An assay that measures the duration of temporal interval of a process that is part of the life of the bearer, where the initial time point of the measured process is the beginning of some transitional state of the bearer such as birth or when planted.
OBI group
PERSON: Alan Ruttenberg
This assay measures time not developmental stage. we recognize that development takes different time periods under different conditions such as media / temperature. For example, age measurement assay of fly age, the output likes 28 days but not mid-life of age at room temperature.
age measurement assay
age since egg laying measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since egg laying, the process of the production of egg(s) by an organism.
MO_767 egg laying
PERSON:Chris Stoeckert, Jie Zheng
age since egg laying measurement datum
age since germination measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since germination, the process consisting of physiological and developmental changes by a seed, spore, pollen grain (microspore), or zygote that occur after release from dormancy, and encompassing events prior to and including the first visible indications of growth.
Definition of germination comes from GO. However, the term is deprecated from GO now because it is a grouping term without biological significance.
MO_590 germination
PERSON:Chris Stoeckert, Jie Zheng
age since germination measurement datum
age since eclosion measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since eclosion, the process of emergence of an adult insect from its pupa or cocoon.
MO_876 eclosion
PERSON:Chris Stoeckert, Jie Zheng
age since eclosion measurement datum
age since sowing measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since sowing, the process of placing a seed or spore in some media with the intention to invoke germination.
MO_748 sowing
PERSON:Chris Stoeckert, Jie Zheng
age since sowing measurement datum
age since coitus measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since coitus, the process of copulation that occurs during the process of sexual reproduction.
MO_783 coitus
PERSON:Chris Stoeckert, Jie Zheng
age since coitus measurement datum
age measurement datum
A time measurement datum that is the result of measurement of age of an organism
In MageTab file, we use
initialTimePoint (a process) + age (a number expected) + TimeUnit (definied in UO, such as year, hour, day, etc.)
Now we use the term label indicating the start time point of measuring the age, (number + TimeUnit) are expected instances of the class
MO_178 Age
PERSON: Alan Ruttenberg, Chris Stoeckert, Jie Zheng
discussed on Nov 15, dev call
All subtype will be defined by textual definition now.
note that we are currently defining subtypes of age measurement datum that specify when the age is relative to, e.g. planting, as we don't have adequate temporal predicates yet.
life of bearer doesn't imply organism
this assay measures time not developmental stage. we recognize that development can take different time periods under different conditions such as media / temperature
age as a quality is dubious; we plan to revisit
stages in development are currently handled with controlled vocabulary, such as 2-somite stage
age measurement datum
age since fertilization measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since fertilization, the process of the union of gametes of opposite sexes during the process of sexual reproduction to form a zygote.
Definition of fertilization comes from GO.
MO_701 fertilization
PERSON:Chris Stoeckert, Jie Zheng
age since fertilization measurement datum
age since birth measurement datum
An age measurement datum that is the result of the measurement of the age of an organism since birth, the process of emergence and separation of offspring from the mother.
MO_710 birth
PERSON:Chris Stoeckert, Jie Zheng
age since birth measurement datum
half life datum (t 1/2)
Bjoern Peters
Bjoern Peters
The time it takes for 50% of a class of stochastic processes to occur.
half life datum (t 1/2)
t 1/2
dose response curve
A data item of paired values, one indicating the dose of a material, the other quantitating a measured effect at that dose. The dosing intervals are chosen so that effect values be interpolated by a plotting a curve.
Bjoern Peters; Randi Vita
dose response curve
half maximal effective concentration (EC50)
Bjoern Peters; Randi Vita
Determining the potentency of a drug / antibody / toxicant by measuring a graded dose response curve, and determining the concentration of the compound where 50% of its maximal effect is observed.
half maximal effective concentration (EC50)
half maximal effective concentration (EC50) is a scalar measurement datum corresponding to the concentration of a compound which induces a response halfway between the baseline and maximum after some specified exposure time.
wikipedia
binding datum
A data item that states if two or more material entities have the disposition to form a complex, and if so, how strong that disposition is.
Bjoern Peters; Randi Vita
binding datum
negative binding datum
A binding datum that states that there is no significant disposition of two or more entities to form a complex
negative binding datum
half maximal inhibitory concentration (IC50)
Bjoern Peters; Randi Vita
Half maximal inhibitory concentration (IC50) is a scalar measurement datum that measures the effectiveness of a compound to competitively inhibit a given process, and corresponds to the concentration of the compound at which it reaches half of its maximum inhibitory effect.
Interpolating that at a dose of IC50=12 nM, half of the binding of a comptetitive ligand is inhibited.
half maximal inhibitory concentration (IC50)
wikipedia
normalization testing design
Person: Chris Stoeckert, Jie Zheng
A study design that tests different normalization procedures.
MO_729 normalization_testing_design
normalization testing design
genetic population background information
Group: OBI group
Group: OBI group
a genetic characteristics information which is a part of genotype information that identifies the population of organisms
genetic population background information
genotype information 'C57BL/6J Hnf1a+/-' in this case, C57BL/6J is the genetic population background information
proposed and discussed on San Diego OBI workshop, March 2011
FWER adjusted p-value
FWER adjusted p-value
A quantitative confidence value resulting from a multiple testing error correction method which adjusts the p-value used as input to control for Type I error in the context of multiple pairwise tests
PERS:Philippe Rocca-Serra
adapted from wikipedia (http://en.wikipedia.org/wiki/Familywise_error_rate)
http://ugrad.stat.ubc.ca/R/library/LPE/html/mt.rawp2adjp.html
wild type organism genotype information
C57BL/6J wild type
Group: OBI group
Group: OBI group
a genotype information about an organism and includes information that there are no known modifications to the genetic background. Generally it is the genotype information of a representative individual from a class of organisms.
proposed and discussed on San Diego OBI workshop, March 2011
wild type organism genotype information
genotype information
Genotype information can be: Mus musculus wild type (in this case the genetic population background information is Mus musculus), C57BL/6J Hnf1a+/- (in this case, C57BL/6J is the genetic population background information and Hnf1a+/- is the allele information
Group: OBI group
Group: OBI group
a genetic characteristics information that is about the genetic material of an organism and minimally includes information about the genetic background and can in addition contain information about specific alleles, genetic modifications, etc.
discussed on San Diego OBI workshop, March 2011
genotype information
allele information
MO_58 Allele
Person: Chris Stoeckert, Jie Zheng
a genetic alteration information that about one of two or more alternative forms of a gene or marker sequence and differing from other alleles at one or more mutational sites based on sequence. Polymorphisms are included in this definition.
allele information
discussed on San Diego OBI workshop, March 2011
genotype information 'C57BL/6J Hnf1a+/-' in this case, Hnf1a+/- is the allele information
post-transcriptional modification design
Person: Chris Stoeckert, Jie Zheng
A study design in which a modification of the transcriptome, proteome (not genome) is made, for example RNAi, antibody targeting.
MO_392 cellular_modification_design
post transcription modification design?
or more clear RNAi design / antibody targeting design?
need to check the use cases
post-transcriptional modification design
genetic alteration information
Group: OBI group
Group: OBI group
a genetic characteristics information that is about known changes or the lack thereof from the genetic background, including allele information, duplication, insertion, deletion, etc.
genetic alteration information
proposed and discussed on San Diego OBI workshop, March 2011
wild type allele information
MO_605 genotype
Person: Chris Stoeckert, Jie Zheng
an allele information that is about the allele found most frequently in natural populations, or in standard laboratory stocks for a given organism.
discussed on San Diego OBI workshop, March 2011
wild type allele information
stimulus or stress design
Person: Chris Stoeckert, Jie Zheng
A study design in which the response of an organism(s) to the stress or stimulus is studied, e.g. osmotic stress, heat shock, radiation exposure, behavioral treatment etc.
MO_568 stimulus_or_stress_design
stimulus or stress design
genetic characteristics information
MO definition:
The genotype of the individual organism from which the biomaterial was derived. Individual genetic characteristics include polymorphisms, disease alleles, and haplotypes.
examples in ArrayExpress
wild_type
MutaMouse (CD2F1 mice with lambda-gt10LacZ integration)
AlfpCre; SNF5 flox/knockout
p53 knock out
C57Bl/6 gp130lox/lox MLC2vCRE/+
fer-15; fem-1
df/df
pat1-114/pat1-114 ade6-M210/ade6-M216 h+/h+ (cells are diploid)
MO_66 IndividualGeneticCharacteristics
Person: Chris Stoeckert, Jie Zheng
a data item that is about genetic material including polymorphisms, disease alleles, and haplotypes.
genetic characteristics information
dose response design
Person: Chris Stoeckert, Jie Zheng
A study design that examines the relationship between the size of the administered dose and the extent of the response.
MO_485 dose_response_design
dose response design
q-value
PMID: 20483222. Comp Biochem Physiol Part D Genomics Proteomics. 2008 Sep;3(3):234-42. Analysis of Sus scrofa liver proteome and identification of proteins differentially expressed between genders, and conventional and genetically enhanced lines.
"After controlling the false discovery rate (FDR</=0.1) using the Storey q value only four proteins (EPHX1, CAT, PAH, ST13) were shown to be differentially expressed between genders (Males/Females) and two proteins (SELENBP2, TAGLN) were differentially expressed between two lines (Transgenic/Conventional pigs)"
q-value
A quantitative confidence value that measures the minimum false discovery rate that is incurred when calling that test significant.
To compute q-values, it is necessary to know the p-value produced by a test and possibly set a false discovery rate level.
Adapted from several sources, including
http://.en/wikipedia.org/wiki/False_discovery_rate
http://svitsrv25.epfl.ch/R-doc/library/qvalue.html
FDR adjusted p-value
PERS:Philippe Rocca-Serra
genetic modification design
Person: Chris Stoeckert, Jie Zheng
A study design in which an organism(s) is studied that has had genetic material removed, rearranged, mutagenized or added, such as in a knock out.
MO_447 genetic_modification_design
genetic modification design
lowess group transformation
A lowess transformation where a potentially different normalization curve is generated and used for two or more groups (delineated by some criteria); criteria could include blocks (e.g. print-tip groups) on an array, or the day on which mass spectrometry was performed.
MO_861 lowess_group_normalization
Person: Elisabetta Manduchi
lowess group transformation
lowess transformation
A data transformation of normalizing ratio data by using a locally weighted polynomial regression (typically after a log transformation). The regression can be performed on log ratios resulting from the relation of two data sets versus the average log intensity data from the same two data sets or it can be performed on raw or log transformed values from one data set versus values from another. The goal could be to remove intensity-dependent dye-specific effects from the set of pair wise ratios. This method can be applied globally, or limited by one or more specified criteria.
MO_720 lowess_normalization
Person: Elisabetta Manduchi
lowess transformation
lowess global transformation
A lowess transformation where the same normalization curve is used for all members of the data set; e.g. Features on an array, picked spots on a gel, or measured metabolites in a sample.
MO_692 lowess_global_normalization
Person: Elisabetta Manduchi
lowess global transformation
sampling time measurement datum
A time measurement datum when an observation is made or a sample is taken from a material as measured from some reference point.
MO_738 timepoint
Person: Chris Stoeckert
sampling time measurement datum
time point
minimal inhibitory concentration
A scalar measurement datum that indicates the lowest concentration at which a specific compound significantly inhibits a process from occurring compared to in the absence of the compound.
Bjoern Peters, coordinated with Albert Goldfain
Created following request by Albert Goldfain
PERSON:Bjoern Peters
minimal inhibitory concentration
PDB file
A 3d structural organization datum capturing the results of X-ray crystallography or NMR experiment that is formatted as specified by the Protein Databank (http://www.wwpdb.org/docs.html). A PDB file can describe the structure of multiple molecules, each of which has a different chain identifier assigned.
PDB file
PERSON: Bjoern Peters, Dorjee Tamang, Jason Greenbaum
The file found in the pdb with the identifier 3pe4
http://www.pdb.org/pdb/download/downloadFile.do?fileFormat=pdb&compression=NO&structureId=3pe4
equilibrium dissociation constant (KD)
A binding constant defined as the ratio of kon over koff (on-rate of binding divided by off-rate)
IEDB
KD = 32 nM is the equilibrium dissociation rate found for peptide SIINFEKL binding to H-2 Kb
PERSON: Bjoern Peters, Randi Vita
equilibrium dissociation constant (KD)
comparative phenotypic assessment
6/1/2012: We will utilize 'comparative qualities' once they are available in BFO2
Interpreting data from assays that evaluate the qualities or dispositions inhering in an organism or organism part and comparing it to data from other organisms to make a conclusion about a phenotypic difference
Philly workshop 2011
Philly workshop 2011
comparative phenotypic assessment
equilibrium association constant (KA)
A binding constant defined as the ratio of koff over kon (off-rate of binding divided by on-rate)
IEDB
KA = 10^-12 M^-1 is the equilibirum association constant maximally found for antibody binding to haptens.
PERSON: Bjoern Peters, Randi Vita
equilibrium association constant (KA)
rate measurement datum
A scalar measurement datum that represents the number of events occuring over a time interval
IEDB
PERSON: Bjoern Peters, Randi Vita
The rate of disassociation of a peptide from a complex with an MHC molecule measured by the ratio of bound and unbound peptide per unit of time.
rate measurement datum
50% dissociation of binding temperature (Tm)
50% dissociation of binding temperature (Tm)
A binding datum that specifies the temperature at which half of the binding partners are forming a complex and the other half are unbound.
IEDB
PERSON: Bjoern Peters, Randi Vita
Preparing a complex of a purified HLA-A*02:01 bound to a specific peptide ligand, varying the temperature while detecting the fraction of bound complexes with a complex conformation specific antibody, and interpolating the temperature at which 50% of complexes are dissociated.
melting temperature (Tm)
equilibrium dissociation constant (KD) approximated by IC50
A measurement of an IC50 value under specific assay conditions approximates KD, namely the binding reaction is at an equilibrium, there is a single population of sites on the receptor that competitor and ligand are binding to, and the concentration of the receptor must be much less than the KD for the competitor and the ligand. In this case, according to Cheng and Prussoff, KD = IC50 / (1 + Lstot / KDs), in which Lstot is the total concentration of the labeled competitor and KDs is the KD value of that competitor.
PERSON: Bjoern Peters, Randi Vita
equilibrium dissociation constant (KD) approximated by IC50
http://dx.doi.org/10.1016/0006-2952(73)90196-2
DNA sequence data
8/29/11 call: This is added after a request from Melanie and Yu. They should review it further. This should be a child of 'sequence data', and as of the current definition will infer there.
A sequence data item that is about the primary structure of DNA
DNA sequence data
OBI call; Bjoern Peters
OBI call; Melanie Courtout
The part of a FASTA file that contains the letters ACTGGGAA
assigning gene property based on phenotypic assessment
Interpreting data from assays that evaluate the qualities or dispositions inhering in an organism or organism part and comparing it to data from other organisms that have a defined genetic difference, and assigning a property to the product of the targeted gene as a result.
Philly workshop 2011
Philly workshop 2011
assigning gene property based on phenotypic assessment
equilibrium dissociation constant (KD) approximated by EC50
A measurement of an EC50 value under specific assay conditions approximates KD, namely the binding reaction is at an equilibrium, and the concentration of the receptor must be much less than the KD for the ligand.
Assay Development: Fundamentals and Practices, By Ge Wu, page 74
PERSON: Bjoern Peters, Randi Vita
equilibrium dissociation constant (KD) approximated by EC50
half life of binding datum
A half life datum of the time it takes for 50% of bound complexes in an ensemble to disassociate in absence of re-association.
IEDB
PERSON: Bjoern Peters, Randi Vita
The 45 minute period in which one half of the complexes formed by peptide ligand bound to a HLA-A*0201molecule disassociate.
half life of binding datum
binding
9/28/11 BP: The disposition referenced is the one of the ligand to bind the molecule. This along with binding as a function / process needs to be figured out with GO which is inconsistent at this point.
A peptide binding to an MHC molecule to form a complex.
IEDB
PERSON: Bjoern Peters, Randi Vita
The process of material entities forming complexes.
binding
PDB file chain
A 3D structural organization datum that is part of a PDB file and has a specific chain identifier that identifies the entire information on a subset of the material entities
IEDB
PDB file chain
PERSON: Bjoern Peters, Dorjee Tamang, Jason Greenbaum
The 'D' chain in the PDB file 2BSE identifies the heavy chain of the antibody in the protein:antibody complex
binding off rate measurement datum (koff)
A rate measurement datum of how quickly bound complexes disassociate
IEDB
PERSON: Bjoern Peters, Randi Vita
binding off rate measurement datum (koff)
binding on rate measurement datum (kon)
A rate measurement datum of how quickly bound complexes form
IEDB
PERSON: Bjoern Peters, Randi Vita
binding on rate measurement datum (kon)
average depth of sequence coverage
NIAID GSCID-BRC
Depth of Coverage - Average
An average value of the depth of sequence coverage based both on external (e.g. Cot-based size estimates) and internal (average coverage in the assembly) measures of genome size.
NIAID GSCID-BRC metadata working group
Person: Chris Stoeckert, Jie Zheng
average depth of sequence coverage
specimen collection time measurement datum
NIAID GSCID-BRC
Specimen Collection Date
A time measurement datum that is the measure of the time when the specimens are collected.
NIAID GSCID-BRC metadata working group
Person: Chris Stoeckert, Jie Zheng
collection date
specimen collection time measurement datum
latitude coordinate measurement datum
NIAID GSCID-BRC
A measurement datum that is the measure of the latitude coordinate of a site.
NIAID GSCID-BRC metadata working group
Person: Chris Stoeckert, Jie Zheng
Specimen Collection Location - Latitude
latitude
latitude coordinate measurement datum
longitude coordinate measurement datum
A measurement datum that is the measure of the longitude coordinate of a site.
NIAID GSCID-BRC
NIAID GSCID-BRC metadata working group
Person: Chris Stoeckert, Jie Zheng
Specimen Collection Location - Longitude
longitude
longitude coordinate measurement datum
drawing a conclusion
Concluding that the length of the hypotenuse is equal to the square root of the sum of squares of the other two sides in a right-triangle.
Concluding that a gene is upregulated in a tissue sample based on the band intensity in a western blot. Concluding that a patient has a infection based on measurement of an elevated body temperature and reported headache. Concluding that there were problems in an investigation because data from PCR and microarray are conflicting.
A planned process in which new information is inferred from existing information.
drawing a conclusion
testable hypothesis
Group:2013 Philly Workshop group
An information content entity that expresses an assertion that is intended to be tested.
In the Philly 2013 workshop, we recognized the limitations of "hypothesis textual entity", and we introduced this as more general. The need for the 'textual entity' term going forward is up for future debate.
Group:2013 Philly Workshop group
hypothesis
that fucoidan has a small statistically significant effect on AT3 level but no useful clinical effect as in-vivo anticoagulant, a paraphrase of part of the last paragraph of the discussion section of the paper 'Pilot clinical study to evaluate the anticoagulant activity of fucoidan', by Lowenthal et. al.PMID:19696660
testable hypothesis
conclusion based on data
Group:2013 Philly Workshop group
An information content entity that is inferred from data.
Group:2013 Philly Workshop group
conclusion based on data
In the Philly 2013 workshop, we recognized the limitations of "conclusion textual entity", and we introduced this as more general. The need for the 'textual entity' term going forward is up for future debate.
The conclusion that a gene is upregulated in a tissue sample based on the band intensity in a western blot. The conclusion that a patient has a infection based on measurement of an elevated body temperature and reported headache. The conclusion that there were problems in an investigation because data from PCR and microarray are conflicting.
The following are NOT conclusions based on data: data themselves; results from pure mathematics, e.g. "13 is prime".
categorical value specification
PERSON:Bjoern Peters
categorical value specification
A value specification that is specifies one category out of a fixed number of nominal categories
scalar value specification
1
1
scalar value specification
A value specification that consists of two parts: a numeral and a unit label
PERSON:Bjoern Peters
value specification
This term is currently a descendant of 'information content entity', which requires that it 'is about' something. A value specification of '20g' for a measurement data item of the mass of a particular mouse 'is about' the mass of that mouse. However there are cases where a value specification is not clearly about any particular. In the future we may change 'value specification' to remove the 'is about' requirement.
The value of 'positive' in a classification scheme of "positive or negative"; the value of '20g' on the quantitative scale of mass.
value specification
PERSON:Bjoern Peters
An information content entity that specifies a value within a classification scheme or on a quantitative scale.
organism
10/21/09: This is a placeholder term, that should ideally be imported from the NCBI taxonomy, but the high level hierarchy there does not suit our needs (includes plasmids and 'other organisms')
13-02-2009:
OBI doesn't take position as to when an organism starts or ends being an organism - e.g. sperm, foetus.
This issue is outside the scope of OBI.
GROUP: OBI Biomaterial Branch
A material entity that is an individual living system, such as animal, plant, bacteria or virus, that is capable of replicating or reproducing, growth and maintenance in the right environment. An organism may be unicellular or made up, like humans, of many billions of cells divided into specialized tissues and organs.
WEB: http://en.wikipedia.org/wiki/Organism
animal
fungus
organism
plant
virus
specimen
Biobanking of blood taken and stored in a freezer for potential future investigations stores specimen.
Note: definition is in specimen creation objective which is defined as an objective to obtain and store a material entity for potential use as an input during an investigation.
PERSON: James Malone
PERSON: Philippe Rocca-Serra
A material entity that has the specimen role.
GROUP: OBI Biomaterial Branch
specimen
data transformation
Philippe Rocca-Serra
The application of a clustering protocol to microarray data or the application of a statistical testing method on a primary data set to determine a p-value.
A planned process that produces output data from input data.
Branch editors
Elisabetta Manduchi
Helen Parkinson
James Malone
Melanie Courtot
Richard Scheuermann
Ryan Brinkman
Tina Hernandez-Boussard
data analysis
data processing
data transformation
logistic-log curve fitting
A logistic-log curve fitting is a curve fitting where a curve of the form y=d+((a-d)/(1+(x/c)^b)) is obtained, where a, b, c, and d are determined so to optimize its fit to the input data points (x_1, y_1), (x_2, y_2), ..., (x_n, y_n).
ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1448
Elisabetta Manduchi
James Malone
Melanie Courtot
Ryan Brinkman
Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution. In this case a and d correspond to the theoretical OD of the assay at zero and infinite concentrations, respectively; c is the dilution associated with the point of symmetry of the sigmoid and is located at the midpoint of the assay found at the inflection point of the curve; b is a curvature parameter and is related to the slope of the curve.
logistic-log curve fitting
logit-log curve fitting
A logit-log curve fitting is a curve fitting where first the limits y_0 an y_infty of y when x->0 and x->infinity, respectively, are estimated from the input data points (x_1, y_1), (x_2,y_2), ..., (x_n, y_n). Then a curve with equation log((y-y_0)/(y_infty-y))=a+b log(x) is obtained, where a and b are determined to optimize its fit to the input data points.
ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1448
Elisabetta Manduchi
James Malone
Melanie Courtot
Ryan Brinkman
The above definition refers to the 'fully specified' logit-log model. The reduced form of this, when it is assumed that y_0=0, is named 'partially specified' logit-log model.
Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution. In this case OD_0 (also referred to OD_min) and OD_infty (also referred to OD_max) correspond to the theoretical OD of the assay at zero and infinite concentrations, respectively.
logit-log curve fitting
log-log curve fitting
A log-log curve fitting is a curve fitting where first a logarithmic transformation is applied both to the x and the y coordinates of the input data points (x_1, y_1), (x_2, y_2), ..., (x_n, y_n), and then coefficients a and b are determined to optimize the fit of log(y)=a+b*log(x) to these input data points.
ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1446
Elisabetta Manduchi
James Malone
Melanie Courtot
Ryan Brinkman
Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution.
log-log curve fitting
feature extraction objective
Elisabetta Manduchi
A feature extraction objective is a data transformation objective where the aim of the data transformation is to generate quantified values from a scanned image.
James Malone
TERM: http://mged.sourceforge.net/ontologies/MGEDOntology.owl#feature_extraction
feature extraction objective
biexponential transformation
A biexponential transformation is a data transformation that, for each (one dimensional) real number input x, outputs an approximation (found, e.g. with the Newton's method) to a solution y of the equation B(y)-x=0, where B denotes a b transformation.
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry.
WEB: http://flowcyt.sourceforge.net/gating/latest.pdf
biexponential transformation
box-cox transformation
A box-cox transformation is a data transformation according to the methods of Box and Cox as described in the article Box, G. E. P. and Cox, D.R. (1964) An analysis of transformations. Journal of Royal Statistical Society, Series B, vol. 26, pp. 211-246.
ARTICLE: Box, G. E. P. and Cox, D.R. (1964), "An analysis of transformations", Journal of Royal Statistical Society, Series B, vol. 26, pp. 211-246.
Ryan Brinkman
box-cox transformation
hyperlog transformation
A hyperlog transformation ia a data transformation that, for each (one dimensional) real number input x, outputs an approximation (found, e.g. with the Newton's method) to a solution y of the equation EH(y)-x=0, where EH denotes an eh transformation.
ARTICLE: Bagwell C.B. (2006), "Hyperlog - a flexible log-like transform for negative, zero, and positive valued data", Cytometry A 64, 34-42."
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry
http://flowcyt.sourceforge.net/gating/latest.pdf
hyperlog transformation
loess scale group transformation one-channel
A loess scale group transformation one-channel is a loess scale group transformation consisting in the application of a scale adjustment following a loess group transformation one-channel, to render the M group variances similar.
Elisabetta Manduchi
Loess scale group normalization applied to data from two one-channel expression microarray assays.
OTHER: Editor's adjustment based on MGED Ontology term
loess scale group transformation one-channel
logical transformation
A logical transformation is a data transformation that, for each (one dimensional) real number input x, outputs an approximation (found, e.g. with the Newton's method) to a solution y of the equation S(y)-x=0, where S denotes an s transformation.
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry.
WEB: http://flowcyt.sourceforge.net/gating/latest.pdf
logical transformation
loess scale group transformation two-channel
A loess scale group transformation two-channel is a loess scale group transformation consisting in the application of a scale adjustment following a loess group transformation two-channel, to render the M group variances similar.
Elisabetta Manduchi
Loess scale group normalization applied to data from a two-channel expression microarray assay.
OTHER: Adjusted from MGED Ontology
loess scale group transformation two-channel
loess global transformation one-channel
A loess global transformation one-channel is a loess global transformation in the special case where the input is the result of an MA transformation applied to intensities from two related one-channel assays.
Elisabetta Manduchi
Loess global normalization applied to data from two one-channel expression microarray assays, where the curve is obtained using all reporters. The goal is to remove intensity-dependent biases.
OTHER: Editor's generalization based on MGED Ontology term
loess global transformation one-channel
split-scale transformation
A split-scale transformation is a data transformation which is an application of a function f described as follows to a (one dimensional) real number input. f(x)=a*x+b if x=for x>t; where log denotes a logarithmic transformation and a, b, c, d, r, t are real constants, with a, c, d, r, t positive, chosen so that f is continuous with a continuous derivative at the transition point t.
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry
WEB: http://flowcyt.sourceforge.net/gating/latest.pdf
split-scale transformation
loess global transformation two-channel
A loess global transformation two-channel is a loess global transformation in the special case where the input the result of an MA transformation applied to intensities from the two channels of a two-channel assay.
Elisabetta Manduchi
Loess global normalization applied to data from a two-channel expression microarray assay, where the curve is obtained using all reporters. The goal is to remove intensity-dependent biases.
OTHER: Editor's generalization based on MGED Ontology term
loess global transformation two-channel
sine transformation
A sine transformation is a data transformation which consists in applying the sine function to a (one dimensional) real number input. The sine function is one of the basic trigonometric functions and a definition is provided, e.g., at http://mathworld.wolfram.com/Sine.html.
Elisabetta Manduchi
WEB: http://mathworld.wolfram.com/Sine.html
sine transformation
sine(0)=0, sine(pi/2)=1, sine(pi)=0, sine(3*pi/2)=-1, sine(pi/6)=1/2, sine(x+2*k*pi)=sine(x) where k is any integer, etc.
cosine transformation
Philippe Rocca-Serra
A cosine transformation is a data transformation which consists in applying the cosine function to a (one dimensional) real number input. The cosine function is one of the basic trigonometric functions and a definition is provided, e.g., at http://mathworld.wolfram.com/Cosine.html.
Elisabetta Manduchi
WEB: http://mathworld.wolfram.com/Cosine.html
cosine transformation
cosine(0)=1, cosine(pi/2)=0, cosine(pi)=-1, cosine(3*pi/2)=0, cosine(pi/3)=1/2, cosine(x+2*k*pi)=cosine(x) where k is any integer, etc.
loess group transformation one-channel
A loess group transformation one-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from two related one-channel assays.
A loess group transformation one-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from two related one-channel assays.
Elisabetta Manduchi
OTHER: Editor's generalization based on MGED Ontology term
loess group transformation one-channel
loess group transformation two-channel
A loess group transformation two-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from the two channels of a two-channel assay.
A loess group transformation two-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from the two channels of a two-channel assay.
Elisabetta Manduchi
OTHER: Editor's generalization based on MGED Ontology term
loess group transformation two-channel
homogeneous polynomial transformation
A homogeneous polynomial transformation is a polynomial transformation where all the term of the polynomial have the same degree.
Elisabetta Manduchi
WEB: http://mathworld.wolfram.com/HomogeneousPolynomial.html
a*x, with a non-zero, is a homogeneous polynomial of degree 1 in 1 variable, a*x^2, with a non-zero, is a homogeneous polynomial of degree 2 in 1 variable; a_1*x_1+...+a_n*x_n, with at least one of the a_i's non-zero, is a homogeneous polynomial of degree one in n variables; a*x_n^3+b*x_1*x_2*x_3, with at least one of a and b non-zero, is a homogeneous polynomial of degree 3 in n variables.
homogeneous polynomial transformation
linlog transformation
Philippe Rocca-Serra
A linlog transformation is a data transformation, described in PMID 16646782, whose input is a matrix [y_ik] and whose output is a matrix obtained by applying formula (9) of this paper, where values below an appropriately determined threshold (dependent on the row i) are transformed via a polynomial of degree 1, and values above this threshold are transformed via a logarithm.
Elisabetta Manduchi
PMID: 16646782
This can be used for microarray normalization, e.g. to normalize the data from a two-channel expression microarray assay, as described in PMID 16646782.
linlog transformation
variance stabilizing transformation
A variance stabilizing transformation is a data transformation, described in PMID 12169536, whose input is a matrix [y_ik] and whose output is a matrix obtained by applying formula (6) in this paper. One of the goals is to obtain an output matrix whose rows have equal variances. The method relies on various assumptions described in the paper.
Elisabetta Manduchi
James Malone
Melanie Courtot
PMID: 12169536
This can be used for expression microarray assay normalization and it is referred to as "variance stabilizing normalization", according to the procedure described e.g. in PMID 12169536.
variance stabilising transformation
variance stabilizing transformation
loess global transformation
Philippe Rocca-Serra
A loess global transformation is a loess transformation where only one loess fitting is performed, utilizing one subset of (or possibly all of) the data points in the input so that there is only one resulting loess curve y=f(x) which is used for the transformation.
Elisabetta Manduchi
James Malone
Melanie Courtot
OTHER: Editor's generalization based on MGED Ontology term
loess global transformation
loess group transformation
Philippe Rocca-Serra
A loess group transformation is a loess transformation where the input is partitioned into groups and for each group a loess fitting is performed, utilizing a subset of (or possibly all of) the data points in that group. Thus, a collection of loess curves y=f_i(x) is generated, one per group. Each (x, y) in the input is transformed into (x, y-f_i(x)), where f_i(x) is the curve corresponding to the group to which that data point belongs.
Elisabetta Manduchi
James Malone
Melanie Courtot
OTHER: Editor's generalization based on MGED Ontology term
loess group transformation
loess scale group transformation
A loess scale group transformation is a data transformation consisting in the application of a scale adjustment following a loess group transformation, to render the group variances for the second variable (y) similar. Has objective scaling.
Elisabetta Manduchi
James Malone
Melanie Courtot
OTHER: Editor's generalization based on MGED Ontology term
loess scale group transformation
total intensity transformation single
Philippe Rocca-Serra
A total intensity transformation single is a data transformation that takes as input an n-dimensional (real) vector and multiplies each component of this vector by a coefficient, where the coefficient is obtained by taking the sum of the input components or of a subset of these, multiplied by a constant of choice.
Elisabetta Manduchi
Helen Parkinson
James Malone
Melanie Courtot
Note that if the word "sum" is replaced by the word "mean" in the definition, the resulting definition is equivalent.
OTHER: Adjusted from MGED Ontology
This can be used as a simple normalization method for expression microarray assays. For example, each intensity from a one-channel microarray assay is multiplied by a constant so that the output mean intensity over the microarray equals a desired target T (the multiplicative constant in this case is the T/(mean intensity)).
total intensity transformation single
total intensity transformation paired
Philippe Rocca-Serra
A total intensity transformation paired is a data transformation that takes as input two n-dimensional (real) vectors and multiplies each component of the first vector by a coefficient, where the coefficient is obtained by taking the ratio of the sum of the second input components or of a subset of these by the sum of the first input components or of a subset of these (the same subset is used for the two vectors).
Elisabetta Manduchi
Note that if the word "sum" is replaced by the word "mean" in the definition, the resulting definition is equivalent.
OTHER: Adjusted from MGED Ontology
This can be used as a simple normalization method for the two channels from a two-channel expression microarray assay or from two related one-channel expression microarray assays.
total intensity transformation paired
quantile transformation
A quantile transformation is a data transformation that takes as input a collection of data sets, where each can be thought as an n-dimensional (real) vector, and which transforms each data set so that the resulting output data sets have equal quantiles.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
This can be used for expression microarray assay normalization and it is referred to as "quantile normalization", according to the procedure described e.g. in PMID 12538238.
quantile transformation
mean centering
Philippe Rocca-Serra
A mean centering is a data transformation that takes as input an n-dimensional (real) vector, performs a mean calculation on its components, and subtracts the resulting mean from each component of the input.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
This can be used as a normalization method in expression microarray assays. For example, given a two-channel microarray assay, the log ratios of the two channels (M values) can be mean-centered.
mean centering
mean centring
median centering
Philippe Rocca-Serra
A median centering is a data transformation that takes as input an n-dimensional (real) vector, performs a median calculation on its components, and subtracts the resulting median from each component of the input.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
This can be used as a normalization method in expression microarray assays. For example, given a two-channel microarray assay, the log ratios of the two channels (M values) can be median-centered.
median centering
median centring
differential expression analysis objective
A differential expression analysis objective is a data transformation objective whose input consists of expression levels of entities (such as transcripts or proteins), or of sets of such expression levels, under two or more conditions and whose output reflects which of these are likely to have different expression across such conditions.
Analyses implemented by the SAM (http://www-stat.stanford.edu/~tibs/SAM), PaGE (www.cbil.upenn.edu/PaGE) or GSEA (www.broad.mit.edu/gsea/) algorithms and software
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
differential expression analysis objective
K-fold cross validation method
K-fold cross-validation randomly partitions the original sample into K subsamples. Of the K subsamples, a single subsample is retained as the validation data for testing the model, and the remaining K − 1 subsamples are used as training data. The cross-validation process is then repeated K times (the folds), with each of the K subsamples used exactly once as the validation data. The K results from the folds then can be averaged (or otherwise combined) to produce a single estimation. The advantage of this method over repeated random sub-sampling is that all observations are used for both training and validation, and each observation is used for validation exactly once. 10-fold cross-validation is commonly used
Person:Helen Parkinson
Tina Boussard
K-fold cross validation method
leave one out cross validation method
2009-11-10. Tracker: https://sourceforge.net/tracker/?func=detail&aid=2893049&group_id=177891&atid=886178
Person:Helen Parkinson
The authors conducted leave-one-out cross validation to estimate the strength and accuracy of the differentially expressed filtered genes. http://bioinformatics.oxfordjournals.org/cgi/content/abstract/19/3/368
is a data transformation : leave-one-out cross-validation (LOOCV) involves using a single observation from the original sample as the validation data, and the remaining observations as the training data. This is repeated such that each observation in the sample is used once as the validation data
leave one out cross validation method
jackknifing method
Helen Parkinson
Jacknifing is a re-sampling data transformation process used to estimate the precision of sampling statistics and is a resampling method
http://en.wikipedia.org/wiki/Resampling_%28statistics%29
simple weighting procedure is suggested for combining information over alleles and loci, and sample variances may be estimated by a jackknife procedure
jackknifing
jackknifing method
boostrapping
Although widely accepted that high throughput biological data are typically highly noisy, the effects that this uncertainty has upon the conclusions we draw from these data are often overlooked. However, in order to assign any degree of confidence to our conclusions, we must quantify these effects. Bootstrap resampling is one method by which this may be achieved.
Bootstrapping is a data transformation process which estimates the precision of sampling statistics by drawing randomly with replacement from a set of data points
Helen Parkinson
Bootstrapping is a statistical method for estimating the sampling distribution of a statistic by sampling with replacement from the original data, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio, correlation coefficient or regression coefficient
boostrapping
Benjamini and Hochberg false discovery rate correction method
A data transformation process in which the Benjamini and Hochberg method sequential p-value procedure is applied with the aim of correcting false discovery rate
Helen Parkinson
Helen Parkinson
Statistical significance of the 8 most represented biological processes (GO level 4) among E7 6 month upregulated genes following analysis with DAVID software; Benjamini-Hochberg FDR (false discovery rate)
2011-03-31: [PRS].
specified input and output of dt which were missing
Benjamini and Hochberg false discovery rate correction method
Philippe Rocca-Serra
pareto scaling
A pareto scaling is a data transformation that divides all measurements of a variable by the square root of the standard deviation of that variable.
Elisabetta Manduchi
PMID:16762068
Philippe Rocca-Serra
pareto scaling
modular decomposition
Molecular decomposition is the partition of a network into distinct subgraphs for the purpose of identifying functional clusters. The network data is run through any of several existing algorithms designed to partition a network into distinct subgraphs for the purpose of isolating groups of functionally linked biological elements such as proteins.
Tina Hernandez-Boussard
editor
modular decomposition
k-means clustering
Elisabetta Manduchi
Philippe Rocca-Serra
A k-means clustering is a data transformation which achieves a class discovery or partitioning objective, which takes as input a collection of objects (represented as points in multidimensional space) and which partitions them into a specified number k of clusters. The algorithm attempts to find the centers of natural clusters in the data. The most common form of the algorithm starts by partitioning the input points into k initial sets, either at random or using some heuristic data. It then calculates the mean point, or centroid, of each set. It constructs a new partition by associating each point with the closest centroid. Then the centroids are recalculated for the new clusters, and the algorithm repeated by alternate applications of these two steps until convergence, which is obtained when the points no longer switch clusters (or alternatively centroids are no longer changed).
James Malone
WEB: http://en.wikipedia.org/wiki/K-means
k-means clustering
hierarchical clustering
A hierarchical clustering is a data transformation which achieves a class discovery objective, which takes as input data item and builds a hierarchy of clusters. The traditional representation of this hierarchy is a tree (visualized by a dendrogram), with the individual input objects at one end (leaves) and a single cluster containing every object at the other (root).
James Malone
WEB: http://en.wikipedia.org/wiki/Data_clustering#Hierarchical_clustering
hierarchical clustering
average linkage hierarchical clustering
An average linkage hierarchical clustering is an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the average distance between objects from the first cluster and objects from the second cluster.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
average linkage hierarchical clustering
complete linkage hierarchical clustering
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the maximum distance between objects from the first cluster and objects from the second cluster.
complete linkage hierarchical clustering
single linkage hierarchical clustering
Elisabetta Manduchi
A single linkage hierarchical clustering is an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the minimum distance between objects from the first cluster and objects from the second cluster.
PERSON: Elisabetta Manduchi
single linkage hierarchical clustering
Benjamini and Yekutieli false discovery rate correction method
A data transformation in which the Benjamini and Yekutieli method is applied with the aim of correcting false discovery rate
Helen Parkinson
Helen Parkinson
The expression set was compared univariately between the stroke patients and controls, gene list was generated using False Discovery Rate correction (Benjamini and Yekutieli)
2011-03-31: [PRS].
specified input and output of dt which were missing
Benjamini and Yekutieli false discovery rate correction method
Philippe Rocca-Serra
dimensionality reduction
Philippe Rocca-Serra
data projection
A dimensionality reduction is data partitioning which transforms each input m-dimensional vector (x_1, x_2, ..., x_m) into an output n-dimensional vector (y_1, y_2, ..., y_n), where n is smaller than m.
Elisabetta Manduchi
James Malone
Melanie Courtot
PERSON: Elisabetta Manduchi
PERSON: James Malone
PERSON: Melanie Courtot
dimensionality reduction
principal components analysis dimensionality reduction
Philippe Rocca-Serra
A principal components analysis dimensionality reduction is a dimensionality reduction achieved by applying principal components analysis and by keeping low-order principal components and excluding higher-order ones.
Elisabetta Manduchi
James Malone
Melanie Courtot
PERSON: Elisabetta Manduchi
PERSON: James Malone
PERSON: Melanie Courtot
pca data reduction
principal components analysis dimensionality reduction
probabilistic algorithm
A probabilistic algorithm is one which involves an element of probability or randomness in the transformation of the data.
James Malone
PERSON: James Malone
probabilistic algorithm
expectation maximization
EM is a probabilistic algorithm used to estimate the maximum likelihood of parameters from existing data where the model involves unobserved latent variables. The input to this method is the data model for which the estimation is performed over and the output is an approximated probability function.
James Malone
PERSON: James Malone
expectation maximization
global modularity calculation
A network graph quality calculation in which an input data set of subgraph modules and their in-degree and out-degree qualities is used to calculate the average modularity of subgraphs within the network.
PERSON: Richard Scheuermann
Richard Scheuermann
global modularity calculation
dye swap merge
A dye swap merge is a replicate analysis which takes as input data from paired two-channel microarray assays where the sample labeled with one dye in the first assay is labeled with the other dye in the second assay and vice versa. The output for each reporter is obtained by combining its (raw or possibly pre-processed) M values in the two assays, where the M value in an assay is defined as the difference of the log intensities in the two channels. This can be used as a normalization step, when appropriate assumptions are met.
Elisabetta Manduchi
James Malone
PERSON: Elisabetta Manduchi
PERSON: James Malone
dye swap merge
moving average
Philippe Rocca-Serra
A moving average is a data transformation in which center calculations, usually mean calculations, are performed on values within a sliding window across the input data set.
Elisabetta Manduchi
Helen Parkinson
PERSON: Elisabetta Manduchi
PERSON: Helen Parkinson
The moving average is often used to handle data from tiling arrays.
moving average
replicate analysis
A replicate analysis is a data transformation in which data from replicates are combined, e.g. through descriptive statistics calculations, and the results might be utilized for a variety of purposes, like assessing reproducibility, identifying outliers, normalizing, etc.
Elisabetta Manduchi
Helen Parkinson
PERSON: Helen Parkinson
PERSON:Elisabetta Manduchi
Replicate analysis can be used in microarray analysis to identify and potentially exclude low quality data.
replicate analysis
b cell epitope prediction
A B cell epitope prediction takes as input an antigen sequence, and through an analysis of this sequence, produces as output a prediction of the likelihood the biomaterial is a B Cell Epitope.
Helen Parkinson
PERSON: Helen Parkinson
b cell epitope prediction
mhc binding prediction
An MHC binding prediction takes an input of a biomaterial sequence and through an analysis of this sequence, produces as output a prediction of the likelihood that the biomaterial will bind to an MHC molecule.
Helen Parkinson
PERSON: Helen Parkinson
mhc binding prediction
t cell epitope prediction
A T cell epitope prediction takes as input an antigen sequence, and through an analysis of this sequence, produces as output a prediction of the likelihood the biomaterial is a T cell epitope.
Helen Parkinson
PERSON: Helen Parkinson
t cell epitope prediction
data imputation
ARTICLE: Little, RJA and Rubin, DB (2002). Statistical Analysis with Missing Data, Second Edition. John Wiley: Hoboken New Jersey, pp. 59-60.
Imputation is a means of filling in missing data values from a predictive distribution of the missing values. The predictive distribution can be created either based on a formal statistical model (i,e, a multivariate normal distribution) or an algorithm.
Monnie McGee
data imputation
continuum mass spectrum
PERSON: James Malone
A continuum mass spectrum is a data transformation that contains the full profile of the detected signals for a given ion.
PERSON: Tina Boussard
PERSON: Tina Hernandez-Boussard
continuum mass spectrum
characteristic path length calculation
PERSON: Tina Hernandez-Boussard
PERSON: Tina Hernandez-Boussard
Quantifying subgraph navigability based on shortest-path length averaged over all pairs of subgraph vertices
characteristic path length calculation
centroid mass spectrum
centroid mass spectrum calculation
centroiding
A centroid mass spectrum is a data transformation in which many points are used to delineate a mass spectral peak, is converted into mass-centroided data by a data compression algorithm. The centroided mass peak is located at the weighted center of mass of the profile peak. The normalized area of the peak provides the mass intensity data.
Person:Tina Hernandez-Boussard
centroid mass spectrum
centroid mass spectrum
Holm-Bonferroni family-wise error rate correction method
Person:Helen Parkinson
WEB: http://en.wikipedia.org/wiki/Holm%E2%80%93Bonferroni_method
a data transformation that performs more than one hypothesis test simultaneously, a closed-test procedure, that controls the familywise error rate for all the k hypotheses at level α in the strong sense. Objective: multiple testing correction
t-tests were used with the type I error adjusted for multiple comparisons, Holm's correction (HOLM 1979), and false discovery rate, http://www.genetics.org/cgi/content/full/172/2/1179
2011-03-14: [PRS]. Class Label has been changed to address the conflict with the definition
Also added restriction to specify the output to be a FWER adjusted p-value
The 'editor preferred term' should be removed
Holm-Bonferroni family-wise error rate correction method
Philippe Rocca-Serra
edge weighting
Edge weighting is the substitution or transformation of edge length using numerical data. Data input include a symmetric adjacency matrix for a network and a second data set, for example a list of interactor pairs and a confidence score associated with the experimental detection of each pair's interaction. Each element in the adjacency matrix is transformed or replaced with the corresponding number in the second data set. Output data are a modified adjacency matrix reflecting the transformed state of the network.
Tina Hernandez-Boussard
edge weighting
editor
was classified under algorithm class which is not acceptable super-class
TO BE DEALT WITH STILL BY RICHARD. JAMES
loess transformation
Philippe Rocca-Serra
A loess transformation is a data transformation that takes as input a collection of real number pairs (x, y) and, after performing (one or more) loess fittings, utilizes the resulting curves to transform each (x, y) in the input into (x, y-f(x)) where f(x) is one of the fitted curves.
Elisabetta Manduchi
James Malone
Melanie Courtot
OTHER: Editor's generalization based on MGED Ontology term
loess transformation
curve fitting data transformation
A curve fitting is a data transformation that has objective curve fitting and that consists of finding a curve which matches a series of data points and possibly other constraints.
Elisabetta Manduchi
James Malone
Melanie Courtot
WEB: http://en.wikipedia.org/wiki/Curve_fitting
curve fitting data transformation
family wise error rate correction method
A family wise error rate correction method is a multiple testing procedure that controls the probability of at least one false positive.
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 19
Monnie McGee
2011-03-31: [PRS].
creating a defined class by specifying the necessary output of dt
allows correct classification of FWER dt
FWER correction
Philippe Rocca-Serra
family wise error rate correction method
submatrix extraction
A submatrix extraction is a projection whose input is a matrix and whose output is a matrix obtained by selecting certain rows and columns from the input. (Note that, if one represents the input matrix as a vector obtained by concatenating its rows, then extracting a submatrix is equivalent to projecting this vector into that composed by the entries belonging to the rows and columns of interest from the input matrix.)
Elisabetta Manduchi
James Malone
Melanie Courtot
Note that this can be considered as a special case of projection if one represents the input matrix as a vector obtained by concatenating its rows. Then extracting a submatrix is equivalent to projecting this vector into the entries belonging to the rows and columns of interest from the input matrix.
WEB: http://en.wikipedia.org/wiki/Submatrix
When presented with the data from an expression microarray experiment in the form of a matrix, whose rows correspond to genes and whose columns correspond to samples, if one filters some of the genes and/or some of the samples out, the resulting data set corresponds to a submatrix of the original set.
submatrix extraction
row submatrix extraction
A row submatrix extraction is a submatrix extraction where all the columns of the input matrix are retained and selection only occurs on the rows.
Elisabetta Manduchi
James Malone
Melanie Courtot
PERSON: Elisabetta Manduchi
PERSON: James Malone
PERSON: Melanie Courtot
When presented with the data from an expression microarray experiment in the form of a matrix, whose rows correspond to genes and whose columns correspond to samples, if one filters some of the genes out, the resulting data set corresponds to a row submatrix of the original set.
row submatrix extraction
column submatrix extraction
A column submatrix extraction is a submatrix extraction where all the rows of the input matrix are retained and selection only occurs on the columns.
Elisabetta Manduchi
James Malone
Melanie Courtot
PERSON: Elisabetta Manduchi
PERSON: James Malone
PERSON: Melanie Courtot
When presented with the data from an expression microarray experiment in the form of a matrix, whose rows correspond to genes and whose columns correspond to samples, if one filters some of the samples out, the resulting data set corresponds to a column submatrix of the original set.
column submatrix extraction
gating
Gating is a property-based vector selection with the objective of partitioning a data vector set into vector subsets based on dimension values of individual vectors (events), in which vectors represent individual physical particles (often cells) of a sample and dimension values represent light intensity qualities as measured by flow cytometry.
James Malone
Josef Spidlen
Melanie Courtot
PERSON: James Malone
PERSON: Josef Spidlen
PERSON: Richard Scheuermann
PERSON: Ryan Brinkman
PERSON:Melanie Courtot
Richard Scheuermann
Ryan Brinkman
gating
descriptive statistical calculation objective
A descriptive statistical calculation objective is a data transformation objective which concerns any calculation intended to describe a feature of a data set, for example, its center or its variability.
Elisabetta Manduchi
James Malone
Melanie Courtot
Monnie McGee
PERSON: Elisabetta Manduchi
PERSON: James Malone
PERSON: Melanie Courtot
PERSON: Monnie McGee
descriptive statistical calculation objective
mean calculation
Philippe Rocca-Serra
A mean calculation is a descriptive statistics calculation in which the mean is calculated by taking the sum of all of the observations in a data set divided by the total number of observations. It gives a measure of the 'center of gravity' for the data set. It is also known as the first moment.
From Monnie's file comments - need to add moment_calculation and center_calculation roles but they don't exist yet - (editor note added by James Jan 2008)
James Malone
Monnie McGee
PERSON: James Malone
PERSON: Monnie McGee
mean calculation
network analysis
network topology analysis
A data transformation that takes as input data that describes biological networks in terms of the node (a.k.a. vertex) and edge graph elements and their characteristics and generates as output properties of the constituent nodes and edges, the sub-graphs, and the entire network.
PERSON: Richard Scheuermann
Richard Scheuermann
network analysis
sequence analysis objective
James Malone
PERSON: James Malone
A sequence analysis objective is a data transformation objective which aims to analyse some ordered biological data for sequential patterns.
sequence analysis objective
longitudinal data analysis
PERSON: James Malone
PERSON: Tina Boussard
correlation analysis
Longitudinal analysis is a data transformation used to perform repeated observations of the same items over long periods of time.
longitudinal data analysis
longitudinal data analysis
survival analysis objective
A data transformation objective which has the data transformation aims to model time to event data (where events are e.g. death and or disease recurrence); the purpose of survival analysis is to model the underlying distribution of event times and to assess the dependence of the event time on other explanatory variables
Kaplan meier data transformation
PERSON: James Malone
PERSON: Tina Boussard
http://en.wikipedia.org/wiki/Survival_analysis
survival analysis
survival analysis objective
mass spectrometry analysis
A data transformation which has the objective of spectrum analysis.
mass spectrometry analysis
spread calculation data transformation
EDITOR
A spread calculation is a data transformation that has objective spread calculation.
James Malone
spread calculation data transformation
Kaplan Meier
PERSON: James Malone
PERSON: Tina Boussard
a nonparametric (actuarial) data transformation technique for estimating time-related events. It is a univariate analysis that estimates the probability of the proportion of subjects in remission at a particular time, starting from the initiation of active date (time zero), and takes into account those lost to follow-up or not yet in remission at end of study (censored)
http://en.wikipedia.org/wiki/Kaplan%E2%80%93Meier_estimator
Kaplan Meier
multiple testing correction method
A multiple testing correction method is a hypothesis test performed simultaneously on M > 1 hypotheses. Multiple testing procedures produce a set of rejected hypotheses that is an estimate for the set of false null hypotheses while controlling for a suitably define Type I error rate
Monnie McGee
PAPER: Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 9-10.
multiple testing correction method
multiple testing procedure
inter-rater reliability objective
A study was conducted to determine the inter-rater reliability of common clinical examination procedures proposed to identify patients with lumbar segmental instability.
Examples include joint-probability of agreement, Cohen's kappa and the related Fleiss' kappa, inter-rater correlation, concordance correlation coefficient and intra-class correlation.
Person:Alan Ruttenberg
Person:Helen Parkinson
a data transformation objective of determining the concordance or agreement between human judges.
http://en.wikipedia.org/wiki/Inter-rater_reliability
inter-rater agreement
inter-rater reliability objective
Westfall and Young family wise error rate correction
Helen Parkinson
Is a data transformation process in which the Westfall and Young method is applied with the aim of controlling for multiple testing
2011-03-31: [PRS].
specified input and output of dt which were missing
PRS: 2011-03-31: set specified input and specified output to the data transformation
Westfall and Young FWER correction
Westfall and Young family wise error rate correction
polynomial transformation
A polynomial transformation is a data transformation that is obtained through a polynomial, where a polynomial is a mathematical expression involving a sum of powers in one or more variables multiplied by coefficients (e.g. see http://mathworld.wolfram.com/Polynomial.html). The number of variables and the degree are properties of a polynomial. The degree of a polynomial is the highest power of its terms, where the terms of a polynomial are the individual summands with the coefficients omitted.
Elisabetta Manduchi
WEB: http://mathworld.wolfram.com/Polynomial.html
a*x+b, with a non-zero, is a polynomial of degree one in one variable; a*x^2+b*x+c, with a nonzero, is a polynomial of degree 2 in 1
variable; a*x*y+b*y+c, with a non-zero, is a polynomial of degree 2 in 2 variables (x and y); a_1*x_1+...+a_n*x_n+b, with at least one of the a_i's non-zero, is a polynomial of degree one in n variables
polynomial transformation
logarithmic transformation
A logarithmic transformation is a data transformation consisting in the application of the logarithm function with a given base a (where a>0 and a is not equal to 1) to a (one dimensional) positive real number input. The logarithm function with base a can be defined as the inverse of the exponential function with the same base. See e.g. http://en.wikipedia.org/wiki/Logarithm.
Elisabetta Manduchi
WEB: http://en.wikipedia.org/wiki/Logarithm
logarithmic transformation
exponential transformation
An exponential transformation is a data transformation consisting in the application of the exponential function with a given base a (where a>0 and a is typically not equal to 1) to a (one dimensional) real number input. For alternative definitions and properties of this function see, e.g., http://en.wikipedia.org/wiki/Exponential_function and http://en.wikipedia.org/wiki/Characterizations_of_the_exponential_function.
Elisabetta Manduchi
WEB: http://en.wikipedia.org/wiki/Characterizations_of_the_exponential_function
WEB: http://en.wikipedia.org/wiki/Exponential_function
exponential transformation
non-negative matrix factorization
Non negative matrix factorization is a data transformation in which factorises a matrix and which forces that all elements must be equal to or greater than zero.
Non-negative matrix factorization is used in text mining where document-term matrix is constructed with the weights of various terms (typically weighted word frequency information) from a set of documents. This matrix is factored into a term-feature and a feature-document matrix.
http://en.wikipedia.org/wiki/Non-negative_matrix_factorization
non-negative matrix factorization
soft independent modeling of class analogy analysis
SIMCA
Soft independent modeling by class analogy (SIMCA) is a descriptive statistics method for supervised classification of data. The method requires a training data set consisting of samples (or objects) with a set of attributes and their class membership. The term soft refers to the fact the classifier can identify samples as belonging to multiple classes and not necessarily producing a classification of samples into non-overlapping classes.
Tina Hernandez-Boussard
WEB: http://en.wikipedia.org/wiki/Soft_independent_modelling_of_class_analogies
soft independent modeling of class analogy analysis
discriminant function analysis
Discriminant function analysis is a form of discriminant analysis used to determine which variables discriminate between two or more naturally occurring groups. Analysis is used to determine which variable(s) are the best predictors of a particular outcome.
Tina Hernandez-Boussard
WEB: http://www.statsoft.com/textbook/stdiscan.html
discriminant function analysis
canonical variate analysis
CVA
Tina Hernandez-Boussard
WEB: http://en.wikipedia.org/wiki/Canonical_analysis
canonical variate analysis
canonical variate analysis is a form of discriminant analysis that takes several continuous predictor variables and uses the entire set to predict several criterion variables, each of which is also continuous. CVA simultaneously calculates a linear composite of all x variables and a linear composite of all y variables. Unlike other multivariate techniques, these weighted composites are derived in pairs. Each linear combination is called a canonical variate and takes the general linear form.
linear discriminant functional analysis
Linear discriminant functional analysis (LDFA) is a multivariate technique used in special applications where there are several intact groups (random assignment may be impossible) and they have been measured on several independent measures. Thus, you will want to describe how these groups differ on the basis of these measures. In this case, classification and prediction is the main objective.
PERSON: Tina Hernandez-Boussard
Tina Hernandez-Boussard
linear discriminant functional analysis
regression analysis method
BOOK: Richard A. Berk, Regression Analysis: A Constructive Critique, Sage Publications (2004) 978-0761929048
Regression analysis is a descriptive statistics technique that examines the relation of a dependent variable (response variable) to specified independent variables (explanatory variables). Regression analysis can be used as a descriptive method of data analysis (such as curve fitting) without relying on any assumptions about underlying processes generating the data.
Tina Hernandez-Boussard
regression analysis method
multiple linear regression analysis
Tina Hernandez-Boussard
WEB:http://en.wikipedia.org/wiki/Linear_regression
multiple linear regression analysis
multiple linear regression is a regression method that models the relationship between a dependent variable Y, independent variables Xi, i = 1, ..., p, and a random term epsilon. The model can be written as
Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \cdots +\beta_p X_p + \varepsilon
where \beta_0 = 0 is the intercept ("constant" term), the \beta_i s are the respective parameters of independent variables, and p is the number of parameters to be estimated in the linear regression.
principal component regression
The Principal Component Regression method is a regression analysis method that combines the Principal Component Analysis (PCA)spectral decomposition with an Inverse Least Squares (ILS) regression method to create a quantitative model for complex samples. Unlike quantitation methods based directly on Beer's Law which attempt to calculate the absorbtivity coefficients for the constituents of interest from a direct regression of the constituent concentrations onto the spectroscopic responses, the PCR method regresses the concentrations on the PCA scores.
Tina Hernandez-Boussard
WEB: : http://www.thermo.com/com/cda/resources/resources_detail/1,2166,13414,00.html
principal component regression
partial least square regression analysis
ARTICLE: de Jong, S. (1993). SIMPLS: An alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18: 251-263.
PLS-RA
Partial least squares regression is an extension of the multiple linear regression model (see, e.g., Multiple Regression or General Stepwise Regression). In its simplest form, a linear model specifies the (linear) relationship between a dependent (response) variable Y, and a set of predictor variables, the X's, so that
Y = b0 + b1X1 + b2X2 + ... + bpXp
In this equation b0 is the regression coefficient for the intercept and the bi values are the regression coefficients (for variables 1 through p) computed from the data.
Tina Hernandez-Boussard
partial least square regression analysis
discriminant analysis
Discriminant function analysis is used to determine which variables discriminate between two or more naturally occurring groups. Analysis is used to determine which variable(s) are the best predictors of a particular outcome.
Tina Hernandez-Boussard
WEB: http://www.statsoft.com/textbook/stdiscan.html
discriminant analysis
partial least square discriminant analysis
PLS Discriminant Analysis (PLS-DA) is a discriminant analysis performed in order to sharpen the separation between groups of observations, by hopefully rotating PCA (Principal Components Analysis) components such that a maximum separation among classes is obtained, and to understand which variables carry the class separating information.
WEB: http://www.camo.com/rt/Resources/pls-da.html
James Malone
PLS-DA
partial least square discriminant analysis
eh transformation
An eh transformation is a data transformation obtained by applying the function EH described in what follows to a (one dimensional) real number input. EH(x)=exp(x*d/r)+b*(d/r)*x-1, if x>=0, and EH(x)=-exp(-x*d/r)+b*(d/r)*x+1, otherwise. Here exp denotes an exponential transformation and b, d, r are positive real constants with the objective of normalization.
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry.
WEB: http://flowcyt.sourceforge.net/gating/latest.pdf
eh transformation
b transformation
A b transformation is a data transformation obtained by applying the function B described in what follows to a (one dimensional) real number input. B(x)= a*exp(b*x)-c*exp(-d*x)+f, where exp denotes an exponential transformation and a, b, c, d, f are real constants with a, b, c, d positive with the objective of normalization.
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry.
WEB: http://flowcyt.sourceforge.net/gating/latest.pdf
b transformation
s transformation
An s transformation is a data transformation obtained by applying the function S described in what follows to a (one dimensional) real number input. S(x)=T*exp(w-m)*(exp(x-w)-(p^2)*exp((w-x)/p)+p^2-1) if x>=w, S(x)=-S(w-x) otherwise; where exp denotes an exponential_transformations, 'p^' denotes the exponential transformation with base p; T, w, m, p are real constants with T, m, and p positive and w non-negative, and where w and p are related by w=2p*ln(p)(p+1) with the objective of normalization.
Elisabetta Manduchi
Joseph Spliden
Ryan Brinkman
This type of transformation is typically used in flow cytometry.
WEB: http://flowcyt.sourceforge.net/gating/latest.pdf
s transformation
data visualization
Generation of a heatmap from a microarray dataset
Possible future hierarchy might include this:
information_encoding
>data_encoding
>>image_encoding
data encoding as image
An planned process that creates images, diagrams or animations from the input data.
Elisabetta Manduchi
James Malone
Melanie Courtot
PERSON: Elisabetta Manduchi
PERSON: James Malone
PERSON: Melanie Courtot
PERSON: Tina Boussard
Tina Boussard
data visualization
visualization
similarity calculation
A similarity calculation is a data transformation that attaches to each pair of objects in the input a number that is meant to reflect how 'close' or 'similar' those objects are.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
similarity calculation
euclidean distance calculation
An euclidean distance calculation is a similarity calculation that attaches to each pair of real number vectors of the same dimension n the square root of the sum of the square differences between corresponding components. The smaller this number, the more similar the two vectors are considered.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
euclidean distance calculation
pearson correlation coefficient calculation
A pearson correlation coefficient calculation is a similarity calculation which attaches to each pair of random variables X and Y the ratio of their covariance by the product of their standard deviations. Given a series of n measurements of X and Y written as x_i and y_i where i = 1, 2, ..., n, then their Pearson correlation coefficient refers to the "sample correlation coefficient" and is written as the sum over i of the ratios (x_i-xbar)*(y_i-ybar)/((n-1)*s_x*s_y) where xbar and ybar are the sample means of X and Y , s_x and s_y are the sample standard deviations of X and Y. The closer the pearson correlation coefficient is to 1, the more similar the inputs are considered.
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
WEB: http://en.wikipedia.org/wiki/Correlation
pearson correlation coefficient calculation
loess fitting
Philippe Rocca-Serra
A loess fitting is a curve fitting obtained by localized regression. The latter refers to fitting a polynomial (straight line, quadratic, cubic, etc) to data values within a window covering a fraction of the total number of observations. As the window slides along the axis, a new polynomial is fit to the observations falling within the window. This continues until all points are fit with a local polynomial. The results are then smoothed together to form a curve. The smoothness of loess fits is controlled by a smoothing parameter (often denoted as alpha, usually between 1/4 and 1) and the degree of the polynomial that is fitted by the method (usually denoted by lambda).
ARTICLE: Mathematical details of loess fits are given in Cleveland, William (1993) Visualizing Data. Hobart Press, Summit, New Jersey, pp. 94-101.
Monnie McGee
loess fitting
mode calculation
A mode calculation is a descriptive statistics calculation in which the mode is calculated which is the most common value in a data set. It is most often used as a measure of center for discrete data.
From Monnie's file comments - need to add center_calculation role but it doesn't exist yet - (editor note added by James Jan 2008)
James Malone
Monnie McGee
PERSON: James Malone
PERSON: Monnie McGee
mode calculation
quantile calculation
A quantile calculation is a descriptive statistics calculation in which the kth quantile is the data value for which an approximate k fraction of the data is less than or equal to that value. See http://www.stat.wvu.edu/SRS/Modules/Quantiles/quantiles.html for details.
Monnie McGee
WEB: http://www.stat.wvu.edu/SRS/Modules/Quantiles/quantiles.html
quantile calculation
median calculation
A median calculation is a descriptive statistics calculation in which the midpoint of the data set (the 0.5 quantile) is calculated. First, the observations are sorted in increasing order. For an odd number of observations, the median is the middle value of the sorted data. For an even number of observations, the median is the average of the two middle values.
From Monnie's file comments - need to add center_calculation role but it doesn't exist yet - (editor note added by James Jan 2008)
James Malone
Monnie McGee
PERSON: James Malone
PERSON: Monnie McGee
median calculation
variance calculation
A variance calculation is a descriptive statistics calculation in which the variance is defined as the average squared distance of each observation in the data set to the mean of the data set. It is also known as the second central moment.
From Monnie's file comments - need to add spread_calculation and moment_calculation roles but they don't exist yet - (editor note added by James Jan 2008)
Monnie McGee
PERSON: Monnie McGee
variance calculation
standard deviation calculation
A standard deviation calculation is a descriptive statistics calculation defined as the square root of the variance. Also thought of as the average distance of each value to the mean.
From Monnie's file comments - need to add spread calculation role but they doesn't exist yet - (editor note added by James Jan 2008)
Monnie McGee
PERSON: Monnie McGee
standard deviation calculation
interquartile-range calculation
From Monnie's file comments - need to add spread calculation role but they doesn't exist yet - (editor note added by James Jan 2008)
Monnie McGee
PERSON: Monnie McGee
The interquartile range is a descriptive statistics calculation defined as the difference between the 0.75 quantile and the 0.25 quantile for a set of data.
interquartile-range calculation
skewness calculation
A skewness calculation is a descriptive statistics calculation defined as a parameter that describes how much a distribution (or a data set) varies from a bell-shaped curve. See http://www.riskglossary.com/link/skewness.htm for details. It is also known as the third central moment
From Monnie's file comments - need to add moment calculation role but they doesn't exist yet - (editor note added by James Jan 2008)
Monnie McGee
WEB: http://www.riskglossary.com/link/skewness.htm
skewness calculation
kurtosis calculation
A kurtosis calculation is a descriptive statistics calculation defined as a parameter that measures how large or small the tails of a distribution are relative to the mean. For details, see http://davidmlane.com/hyperstat/A53638.html
From Monnie's file comments - need to add moment calculation role but they doesn't exist yet - (editor note added by James Jan 2008)
Monnie McGee
WEB: http://davidmlane.com/hyperstat/A53638.html
kurtosis calculation
data combination
data pooling
A data transformation in which individual input data elements and values are merged together into a output set of data elements and values.
Richard Scheuermann
data combination
editor
network graph construction
A network analysis in which an input data set describing objects and relationships between objects is transformed into an output representation of these objects as nodes and the relationships as edges of a network graph.
PERSON: Richard Scheuermann
Richard Scheuermann
network graph construction
weighted network graph construction
A network graph construction in which an input data set describing objects and quantitative relationships between objects is transformed into and output representation of these objects as nodes and the quantitative relationships as weighted edges of a network graph.
PERSON: Richard Scheuermann
Richard Scheuermann
weighted network graph construction
directed network graph construction
A network graph construction in which an input data set describing objects and directional relationships between objects is transformed into and output representation of these objects as nodes and the directional relationships as directed edges of a network graph.
PERSON: Richard Scheuermann
Richard Scheuermann
directed network graph construction
node quality calculation
A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of one of the node objects in the network.
PERSON: Richard Scheuermann
Richard Scheuermann
node quality calculation
node degree calculation
A node quality calculation in which an input data set describing object nodes and relationship edges between object nodes is used to enumerate the number of unique relationships of an individual object node.
PERSON: Richard Scheuermann
Richard Scheuermann
node degree calculation
quantitative node degree calculation
A node quality calculation in which an input data set describing object nodes and quantitative relationship edges between object nodes is used to sum all of the quantitative relationships of an individual object node.
PERSON: Richard Scheuermann
Richard Scheuermann
quantitative node degree calculation
node in-degree calculation
A node quality calculation in which an input data set describing object nodes and directional relationship edges between object nodes is used to enumerate the number of unique relationships pointing into an individual object node.
PERSON: Richard Scheuermann
Richard Scheuermann
node in-degree calculation
node out-degree calculation
A node quality calculation in which an input data set describing object nodes and directional relationship edges between object nodes is used to enumerate the number of unique relationships pointing out of an individual object node.
PERSON: Richard Scheuermann
Richard Scheuermann
node out-degree calculation
node shortest path identification
A node quality calculation in which a path describing the shortest path needed to transverse through connected nodes and edges to arrive at a specific target node in the network.
PERSON: Richard Scheuermann
Richard Scheuermann
node shortest path identification
edge quality calculation
A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of one of the edge relationships in the network.
PERSON: Richard Scheuermann
Richard Scheuermann
edge quality calculation
edge betweenness calculation
An edge quality calculation in which the input is a data sets of shortest paths between all pairs of node in the network and the output is the sum of all shortest paths that traverse the specific edge.
PERSON: Richard Scheuermann
Richard Scheuermann
edge betweenness calculation
network subgraph quality calculation
A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of a subgraph partition of the network.
PERSON: Richard Scheuermann
Richard Scheuermann
network subgraph quality calculation
subgraph degree calculation
A network subgraph quality calculation in which an input data set describing subgraphs and relationship edges between subgraphs and other network objects is used to enumerate the number of unique relationships of an individual subgraph.
PERSON: Richard Scheuermann
Richard Scheuermann
subgraph degree calculation
quantitative subgraph degree calculation
A network subgraph quality calculation in which an input data set describing subgraphs and quantitative relationship edges between subgraphs and other network objects is used to sum the quantitative relationships of an individual subgraph.
PERSON: Richard Scheuermann
Richard Scheuermann
quantitative subgraph degree calculation
mathematical feature
PERSON: James Malone
James Malone
This class is temporary and will be placed outside of data transformation ultimately (if it still remains at all after review)
feature is a (parent_class) that describes a characteristic, trait or quality of a data transformation
mathematical feature
log base
Elisabetta Manduchi
The log base is a feature of a logarithmic function which is defined in http://en.wikipedia.org/wiki/Logarithm. Its value can be any positive real number different from 1.
WEB: http://en.wikipedia.org/wiki/Logarithm
logarithm base
logarithmic base
log base
subgraph in-degree calculation
A network subgraph quality calculation in which an input data set describing subgraphs and directional relationship edges between subgraphs and other network objects is used to enumerate the number of unique relationships pointing into an individual subgraph.
PERSON: Richard Scheuermann
Richard Scheuermann
subgraph in-degree calculation
subgraph out-degree calculation
A network subgraph quality calculation in which an input data set describing subgraphs and relationship edges between subgraphs and other network objects is used to enumerate the number of unique relationships pointing out of an individual subgraph.
PERSON: Richard Scheuermann
Richard Scheuermann
subgraph out-degree calculation
intra subgraph connectivity calculation
A network subgraph quality calculation in which an input data set describing internal nodes, edges and node degrees is used to determine the average node degree within the subgraph.
PERSON: Richard Scheuermann
Richard Scheuermann
intra subgraph connectivity calculation
subgraph modularity calculation
A network subgraph quality calculation in which an input data set of subgraph in-degree and out-degree qualities is used to calculate the ratio of indegree to outdegree as a measure of modularity.
PERSON: Richard Scheuermann
Richard Scheuermann
subgraph modularity calculation
network graph quality calculation
A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of the network as a whole.
PERSON: Richard Scheuermann
Richard Scheuermann
network graph quality calculation
unit-variance scaling
A unit-variance scaling is a data transformation that divides all measurements of a variable by the standard deviation of that variable.
Elisabetta Manduchi
PMID:16762068
Philippe Rocca-Serra
autoscaling
unit-variance scaling
MA transformation
An MA transformation is a data transformation which takes as input a collection of data points (g_1, r_1), (g_2, r_2), ..., (g_n, r_n) with the r_i and g_i positive real numbers, and whose output is the collection of data points (A_1, M_1), (A_2, M_2), ..., (A_n, M_n) where, for each i, A_i=(log(g_i)+log(r_i))/2 and M_i=log(r_i)-log(g_i). Here log denotes a logarithmic transformation.
Elisabetta Manduchi
MA transformation
MA transformations are typically used in microarray data analyses. In this context, the g_i and r_i represent the reporter intensities in the two channels of a 2-channel assay or the reporter intensities in two related one-channel assays. Typically the base used for the logarithm is 2.
PERSON: Elisabetta Manduchi
Philippe Rocca-Serra
exponential base
Elisabetta Manduchi
The exponential base is a feature of an exponential function which is defined in http://en.wikipedia.org/wiki/Exponential_function. Its value can be any positive real number (typically different from 1).
WEB: http://en.wikipedia.org/wiki/Exponential_function
exponential base
polynomial degree
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
The polynomial degree is a feature of a polynomial function defined as the highest power of the polynomial's terms, where the terms of a polynomial are the individual summands with the coefficients omitted.
polynomial degree
number of variables
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
The number of variables is a feature of any function (including polynomial functions) with domain contained in an n-dimensional vector space and is defined as n, the dimension of such space.
number of variables
agglomerative hierarchical clustering
Elisabetta Manduchi
bottom-up hierarchical clustering
An agglomerative hierarchical clustering is a hierarchical clustering which starts with separate clusters and then successively combines these clusters until there is only one cluster remaining.
James Malone
PERSON: Elisabetta Manduchi
agglomerative hierarchical clustering
divisive hierarchical clustering
Elisabetta Manduchi
top-down hierarchical clustering
A divisive hierarchical clustering is a hierarchical clustering which starts with a single cluster and then successively splits resulting clusters until only clusters of individual objects remain.
James Malone
PERSON: Elisabetta Manduchi
divisive hierarchical clustering
data partitioning
Data partitioning is a data transformation with the objective of partitioning or separating input data into output subsets.
James Malone
PERSON: Melanie Courtot
PERSON: Richard Scheuermann
PERSON: Ryan Brinkman
data partitioning
data vector reduction objective
James Malone
Data vector reduction is a data transformation objective in which k m-dimensional input vectors are reduced to j m-dimensional output vectors, where j is smaller than k.
PERSON: Richard H. Scheuermann
Richard H. Scheuermann
data vector reduction objective
generalized family wise error rate correction method
A generalized FWER correction method is a multiple testing procedure that controls the probability of at least k+1 false positives, where k is a user-supplied integer.
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 19
Monnie McGee
gFWER correction
generalized family wise error rate correction method
quantile number of false positives correction method
A quantile number of false positives correction method is a MTP that controls for the pth quantile of the distribution of the number of false positives out of the total number of tests performed'
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 19
Monnie McGee
QNFP
quantile number of false positives correction method
tail probability for the proportion of false positives correction method
A TPPFP correction method is a MTP that controls the probability that the proportion of false positives among all rejected hypotheses is no greater than a constant q, where q is between 0 and 1.
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 20
Monnie McGee
TPPFP correction method
tail probability for the proportion of false positives correction method
false discovery rate correction method
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 21 and http://www.wikidoc.org/index.php/False_discovery_rate
Monnie McGee
The false discovery rate is a data transformation used in multiple hypothesis testing to correct for multiple comparisons. It controls the expected proportion of incorrectly rejected null hypotheses (type I errors) in a list of rejected hypotheses. It is a less conservative comparison procedure with greater power than familywise error rate (FWER) control, at a cost of increasing the likelihood of obtaining type I errors. .
2011-03-31: [PRS].
creating a defined class by specifying the necessary output of dt
allows correct classification of FDR dt
FDR correction method
Philippe Rocca-Serra
false discovery rate correction method
proportion of expected false positives correction method
A proportion of expected false positives correction method is a multiple testing procedure that controls the ratio of the expected value of the numbers of false positives to the expected value of the numbers of rejected hypotheses.
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 21
Monnie McGee
PEFP correction method
proportion of expected false positives correction method
quantile proportion of false positives correction method
A quantile proportion of false positives correction method is a multiple testing procedure that controls the pth quantile of the distribution of the proportion of false positives among the rejected hypothesis (false discovery rate).
Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 21
Monnie McGee
QPFP correction method
quantile proportion of false positives correction method
data transformation objective
Modified definition in 2013 Philly OBI workshop
An objective specification to transformation input data into output data
James Malone
PERSON: James Malone
data transformation objective
normalize objective
data normalization objective
Elisabetta Manduchi
Helen Parkinson
PERSON: Elisabetta Manduchi
PERSON: Helen Parkinson
A normalization objective is a data transformation objective where the aim is to remove
systematic sources of variation to put the data on equal footing in order
to create a common base for comparisons.
James Malone
PERSON: James Malone
Quantile transformation which has normalization objective can be used for expression microarray assay normalization and it is referred to as "quantile normalization", according to the procedure described e.g. in PMID 12538238.
data normalization objective
correction objective
PERSON: James Malone
PERSON: Melanie Courtot
A correction objective is a data transformation objective where the aim is to correct for error, noise or other impairments to the input of the data transformation or derived from the data transformation itself
James Malone
Type I error correction
correction objective
normalization data transformation
James Malone
A normalization data transformation is a data transformation that has objective normalization.
PERSON: James Malone
normalization data transformation
averaging data transformation
James Malone
An averaging data transformation is a data transformation that has objective averaging.
PERSON: James Malone
averaging data transformation
partitioning data transformation
James Malone
A partitioning data transformation is a data transformation that has objective partitioning.
PERSON: James Malone
partitioning data transformation
partitioning objective
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
A k-means clustering which has partitioning objective is a data transformation in which the input data is partitioned into k output sets.
A partitioning objective is a data transformation objective where the aim is to generate a collection of disjoint non-empty subsets whose union equals a non-empty input set.
James Malone
partitioning objective
background correction objective
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
A background correction objective is a data transformation objective where the aim is to remove irrelevant contributions from the measured signal, e.g. those due to instrument noise or sample preparation.
James Malone
background correction objective
curve fitting objective
Elisabetta Manduchi
PERSON: Elisabetta Manduchi
A curve fitting objective is a data transformation objective in which the aim is to find a curve which matches a series of data points and possibly other constraints.
James Malone
curve fitting objective
class discovery data transformation
James Malone
clustering data transformation
unsupervised classification data transformation
A class discovery data transformation (sometimes called unsupervised classification) is a data transformation that has objective class discovery.
PERSON: James Malone
class discovery data transformation
Fisher's exact test
Fisher's exact test
Fisher's exact test is a data transformation used to determine if there are nonrandom associations between two Fisher's exact test is a statistical significance test used in the analysis of contingency tables where sample sizes are small where the significance of the deviation from a null hypothesis can be calculated exactly, rather than relying on an approximation that becomes exact in the limit as the sample size grows to infinity, as with many statistical tests.
James Malone
WEB:http://mathworld.wolfram.com/FishersExactTest.html
center calculation objective
PERSON: James Malone
A center calculation objective is a data transformation objective where the aim is to calculate the center of an input data set.
A mean calculation which has center calculation objective is a data transformation in which the center of the input data is discovered through the calculation of a mean average.
James Malone
center calculation objective
class discovery objective
PERSON: Elisabetta Manduchi
PERSON: James Malone
clustering objective
A class discovery objective (sometimes called unsupervised classification) is a data transformation objective where the aim is to organize input data (typically vectors of attributes) into classes, where the number of classes and their specifications are not known a priori. Depending on usage, the class assignment can be definite or probabilistic.
James Malone
class discovery objective
discriminant analysis objective
unsupervised classification objective
class prediction objective
PERSON: Elisabetta Manduchi
PERSON: James Malone
classification objective
A class prediction objective (sometimes called supervised classification) is a data transformation objective where the aim is to create a predictor from training data through a machine learning technique. The training data consist of pairs of objects (typically vectors of attributes) and
class labels for these objects. The resulting predictor can be used to attach class labels to any valid novel input object. Depending on usage, the prediction can be definite or probabilistic. A classification is learned from the training data and can then be tested on test data.
James Malone
class prediction objective
supervised classification objective
spread calculation objective
Person:Helen Parkinson
Spread calculation can be achieved by use of a standard deviation, which measures distance from the mean
is a data transformation objective whereby the aim is to the calculate the spread of a dataset, spread is a descriptive statistic which describes the variability of values in a data set
Awaiting English definition from Monnie McGee
James Malone
spread calculation objective
center calculation data transformation
James Malone
A center calculation data transformation is a data transformation that has objective of center calculation.
PERSON: James Malone
center calculation data transformation
data vector reduction data transformation
A data vector reduction is a data transformation that has objective data vector reduction and that consists of reducing the input vectors k to a smaller number of output vectors j, where j<k.
James Malone
PERSON: James Malone
data vector reduction data transformation
scaling objective
Person:Helen Parkinson
Scaling gene expression data for cross platform analysis http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-454-4_13
is a data transformation objective where all, or some of a data set is adjusted by some data transformation according to some scale, for example a user defined minimum or maximum
Awaiting English definition from Monnie McGee
James Malone
scaling objective
descriptive statistical calculation data transformation
A descriptive statistical calculation data transformation is a data transformation that has objective descriptive statistical calculation and which concerns any calculation intended to describe a feature of a data set, for example, its center or its variability.
James Malone
PERSON: James Malone
descriptive statistical calculation data transformation
scaling data transformation
A scaling data transformation is a data transformation that has objective scaling.
James Malone
PERSON: James Malone
scaling data transformation
error correction objective
Application of a multiple testing correction method
PERSON: James Malone
An error correction objective is a data transformation objective where the aim is to remove (correct for) erroneous contributions arising from the input data, or the transformation itself.
James Malone, Helen Parkinson
error correction objective
sequence analysis data transformation
EDITOR
A sequence analysis data transformation is a data transformation that has objective sequence analysis and has the aim of analysing ordered biological data for sequential patterns.
James Malone
sequence analysis data transformation
cross validation objective
WEB: http://en.wikipedia.org/wiki/Cross_validation
A cross validation objective is a data transformation objective in which the aim is to partition a sample of data into subsets such that the analysis is initially performed on a single subset, while the other subset(s) are retained for subsequent use in confirming and validating the initial analysis.
James Malone
cross validation objective
rotation estimation objective
merging objective
PERSON: Data Transformation Branch
A merging objective is a data transformation objective in which the data transformation has the aim of performing a union of two or more sets.
James Malone
combining objective
merging objective
merging of columns from two different data sets
clustered data visualization
A data visualization which has input of a clustered data set and produces an output of a report graph which is capable of rendering data of this type.
James Malone
clustered data visualization
gene list visualization
Adata visualization which has input of a gene list and produces an output of a report graph which is capable of rendering data of this type.
James Malone
gene list visualization
classified data visualization
A data visualization which has input of a classified data set and produces an output of a report graph which is capable of rendering data of this type.
James Malone
classified data visualization
background corrected data visualization
A data visualization which has input of a background corrected data set and produces an output of a report graph which is capable of rendering data of this type.
James Malone
Monnie McGee
background corrected data visualization
survival analysis data transformation
A data transformation which has the objective of performing survival analysis.
James Malone
PERSON: James Malone
survival analysis data transformation
proportional hazards model estimation
Cox model
Cox proportional hazards model
PERSON: James Malone
PERSON: Tina Boussard
Proportional hazards model is a data transformation model to estimate the effects of different covariates influencing the times-to-failure of a system.
WEB: http://en.wikipedia.org/wiki/Cox_proportional_hazards_model
proportional hazards model estimation
correlation study objective
A data transformation objective in which correlation is obtained (often measured as a correlation coefficient, ρ) which indicates the strength and direction of a relationship between two random variables.
PERSON: Tina Boussard
correlation study objective
spectrum analysis objective
Calculation of characteristic path length in mass spectrometry
PERSON: Tina Boussard
Person:Helen Parkinson
is a data transformation objective where the aim is to analyse some aspect of spectral data by some data transformation process.
spectrum analysis objective
tandem mass spectrometry
A precursor ion is selected in the first stage, allowed to fragment and then all resultant masses are scanned in the second mass analyzer and detected in the detector that is positioned after the second mass analyzer. This experiment is commonly performed to identify transitions used for quantification by tandem MS.
PERSON: James Malone
PERSON: Tina Boussard
PERSON: Tina Boussard
Tandem mass spectrometry is a data transformation that uses two or more analyzers separated by a region in which ions can be induced to fragment by transfer of energy (frequently by collision with other molecules).
tandem mass spectrometry
gas chromatography mass spectrometry
Gas chromatography mass spectrometry is a data transformation combining mass spectrometry and
gas chromatography for the qualitative as well as quantitative
determinations of compounds.
PERSON: James Malone
PERSON: Tina Boussard
PERSON: Tina Boussard
gas chromatography mass spectrometry
chi square test
PERSON: James Malone
PERSON: Tina Boussard
The chi-square test is a data transformation with the objective of statistical hypothesis testing, in which the sampling distribution of the test statistic is a chi-square distribution when the null hypothesis is true, or any in which this is asymptotically true, meaning that the sampling distribution (if the null hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by making the sample size large enough.
chi square test
ANOVA
ANOVA
ANOVA or analysis of variance is a data transformation in which a statistical test of whether the means of several groups are all equal.
James Malone
sequential design
Any design in which the decision as to whether to enroll the next patient, pair of patients, or block of patients is determined by whether the cumulative treatment difference for all previous patients is within specified limits. Enrollment is continued if the difference does not exceed the limits. It is terminated if it does
MUSC
PMID: 17710740.Pharm Stat. 2007 Aug 20.Sequential design approaches for bioequivalence studies with crossover designs.
Philippe Rocca-Serra
Provenance: OCI
sequential design
observation design
OBI branch derived
PMID: 12387964.Lancet. 2002 Oct 12;360(9340):1144-9.Deficiency of antibacterial peptides in patients with morbus Kostmann: an observation study.
Philippe Rocca-Serra
observation design
observation design is a study design in which subjects are monitored in the absence of any active intervention by experimentalists.
genetically modified organism
PERSON: Philippe Rocca-Serra
A protocol for removal of antibiotic resistance cassettes from human embryonic stem cells genetically modified by homologous recombination or transgenesis.
Nat Protoc. 2008;3(10):1550-8. PMID: 18802436
OBI Biomaterial
an organism that is the output of a genetic transformation process
genetically modified organism
predicted data item
BP 12/21: Edited the incomplete definition from Philippe. It is still unclear to me if this should be a data item at all, or an information content entity. This will be important, because if we exclude predictions from data items, we will run into issues that we willl have to duplicate things like 'weight datum' etc. all of which can be predicted.
Philippe Rocca-Serra; Bjoern Peters
A data item that was generated on the basis of a calculation or logical reasoning
predicted data item
mean-centered data
Person:Helen Parkinson
Person:Philippe Rocca-Serra
a data item which has been processed by a mean centering data transformation where each output value is produced by subtracting the mean from the inout value
mean-centered data
group randomization
Philippe Rocca-Serra
adapted from wikipedia [http://en.wikipedia.org/wiki/Randomization]
A group assignment which relies on chance to assign materials to a group of materials in order to avoid bias in experimental set up.
PMID: 18349405. Randomization reveals unexpected acute leukemias in Southwest Oncology Group prostate cancer trial. J Clin Oncol. 2008 Mar 20;26(9):1532-6.
group randomization
prediction
OBI
Philippe Rocca-Serra
Prediction of TF target sites based on atomistic models of protein-DNA complexes. BMC Bioinformatics. 2008 Oct 16;9(1):436. PMID: 18922190
a process by which an event or an entity is described before it actually happens or is being discovered and identified.
prediction
study design
A plan specification comprised of protocols (which may specify how and what kinds of data will be gathered) that are executed as part of an investigation and is realized during a study design execution.
Editor note: there is at least an implicit restriction on the kind of data transformations that can be done based on the measured data available.
PERSON: Chris Stoeckert
a matched pairs study design describes criteria by which subjects are identified as pairs which then undergo the same protocols, and the data generated is analyzed by comparing the differences between the paired subjects, which constitute the results of the executed study design.
experimental design
rediscussed at length (MC/JF/BP). 12/9/08). The definition was clarified to differentiate it from protocol.
study design
repeated measure design
PMID: 10959922.J Biopharm Stat. 2000 Aug;10(3):433-45.Equivalence in test assay method comparisons for the repeated-measure, matched-pair design in medical device studies: statistical considerations.
PlanAndPlannedProcess Branch
a study design which use the same individuals and exposure them to a set of conditions. The effect of order and practice can be confounding factor in such designs
http://www.holah.karoo.net/experimentaldesigns.htm
repeated measure design
cross over design
(source: http://www.sbu.se/Filer/Content0/publikationer/1/literaturesearching_1993/glossary.html)
PMID: 17601993-Objective: HIV-infected patients with lipodystrophy (HIV-lipodystrophy) are insulin resistant and have elevated plasma free fatty acid (FFA) concentrations. We aimed to explore the mechanisms underlying FFA-induced insulin resistance in patients with HIV-lipodystrophy. Research Design and Methods: Using a randomized placebo-controlled cross-over design, we studied the effects of an overnight acipimox-induced suppression of FFA on glucose and FFA metabolism by using stable isotope labelled tracer techniques during basal conditions and a two-stage euglycemic, hyperinsulinemic clamp (20 mU insulin/m(2)/min; 50 mU insulin/m(2)/min) in nine patients with nondiabetic HIV-lipodystrophy. All patients received antiretroviral therapy. Biopsies from the vastus lateralis muscle were obtained during each stage of the clamp. Results: Acipimox treatment reduced basal FFA rate of appearance by 68.9% (52.6%-79.5%) and decreased plasma FFA concentration by 51.6 % (42.0%-58.9%), (both, P < 0.0001). Endogenous glucose production was not influenced by acipimox. During the clamp the increase in glucose-uptake was significantly greater after acipimox treatment compared to placebo (acipimox: 26.85 (18.09-39.86) vs placebo: 20.30 (13.67-30.13) mumol/kg/min; P < 0.01). Insulin increased phosphorylation of Akt (Thr(308)) and GSK-3beta (Ser(9)), decreased phosphorylation of glycogen synthase (GS) site 3a+b and increased GS-activity (I-form) in skeletal muscle (P < 0.01). Acipimox decreased phosphorylation of GS (site 3a+b) (P < 0.02) and increased GS-activity (P < 0.01) in muscle. Conclusion: The present study provides direct evidence that suppression of lipolysis in patients with HIV-lipodystrophy improves insulin-stimulated peripheral glucose-uptake. The increased glucose-uptake may in part be explained by increased dephosphorylation of GS (site 3a+b) resulting in increased GS activity.
Philippe Rocca-Serra
a repeated measure design which ensures that experimental units receive, in sequence, the treatment (or the control), and then, after a specified time interval (aka *wash-out periods*), switch to the control (or treatment). In this design, subjects (patients in human context) serve as their own controls, and randomization may be used to determine the ordering which a subject receives the treatment and control
cross over design
n-to-1 design
Adapted from http://www.childrens-mercy.org/stats/definitions/crossover.htm and source:http://symptomresearch.nih.gov/chapter_6/sec1/csss1pg1.htm)
N-of-1 design is a cross-over design in which the same patient is repeatedly randomised to receive either the experimental treatment or its control (Senn, 1993).
Philippe Rocca-Serra
n-to-1 design
randomized complete block design
A randomized complete block design is_a study design which assigns randomly treatments to block. The number of units per block equals the number of treatment so each block receives each treatment exactly once (hence the qualifier 'complete'). The design was originally devised from field trials used in agronomy and agriculture. The analysis assumes that there is no interaction between block and treatment. The method was then used in other settings So The randomised complete block design is a design in which the subjects are matched according to a variable which the experimenter wishes to control. The subjects are put into groups (blocks) of the same size as the number of treatments. The members of each block are then randomly assigned to different treatment groups.
Philippe Rocca-Serra
http://www.stats.gla.ac.uk/steps/glossary/anova.html,(A researcher is carrying out a study of the effectiveness of four different skin creams for the treatment of a certain skin disease. He has eighty subjects and plans to divide them into 4 treatment groups of twenty subjects each. Using a randomised blocks& design, the subjects are assessed and put in blocks of four according to how severe their skin condition is; the four most severe cases are the first block, the next four most severe cases are the second block, and so on to the twentieth block. The four &members of each block are then randomly assigned, one to each of the four treatment groups. http://www.stats.gla.ac.uk/steps/glossary/anova.html#rbd))
http://www.tufts.edu/~gdallal/ranblock.htm
randomized complete block design
latin square design
Adapted from: http://www.itl.nist.gov/div898/handbook/pri/section3/pri3321.htm and
Latin square design is_a study design which allows in its simpler form controlling 2 levels of nuisance variables (also known as blocking variables).he 2 nuisance factors are divided into a tabular grid with the property that each row and each column receive each treatment exactly once.
PMID: 17582121-Our objective was to examine the effects of dietary cation-anion difference (DCAD) with different concentrations of dietary crude protein (CP) on performance and acid-base status in early lactation cows. Six lactating Holstein cows averaging 44 d in milk were used in a 6 x 6 Latin square design with a 2 x 3 factorial arrangement of treatments: DCAD of -3, 22, or 47 milliequivalents (Na + K - Cl - S)/100 g of dry matter (DM), and 16 or 19% CP on a DM basis. Linear increases with DCAD occurred in DM intake, milk fat percentage, 4% fat-corrected milk production, milk true protein, milk lactose, and milk solids-not-fat. Milk production itself was unaffected by DCAD. Jugular venous blood pH, base excess and HCO3(-) concentration, and urine pH increased, but jugular venous blood Cl- concentration, urine titratable acidity, and net acid excretion decreased linearly with increasing DCAD. An elevated ratio of coccygeal venous plasma essential AA to nonessential AA with increasing DCAD indicated that N metabolism in the rumen was affected, probably resulting in more microbial protein flowing to the small intestine. Cows fed 16% CP had lower urea N in milk than cows fed 19% CP; the same was true for urea N in coccygeal venous plasma and urine. Dry matter intake, milk production, milk composition, and acid-base status did not differ between the 16 and 19% CP treatments. It was concluded that DCAD affected DM intake and performance of dairy cows in early lactation. Feeding 16% dietary CP to cows in early lactation, compared with 19% CP, maintained lactation performance while reducing urea N excretion in milk and urine.
Philippe Rocca-Serra
latin square design
graeco latin square design
Adapted from: http://www.itl.nist.gov/div898/handbook/pri/section3/pri3321.htm and
Greco-Latin square design is a study design which relates to Latin square design
PMID: 6846242-Beaton et al (Am J Clin Nutr 1979;32:2546-59) reported on the partitioning of variance in 1-day dietary data for the intake of energy, protein, total carbohydrate, total fat, classes of fatty acids, cholesterol, and alcohol. Using the same food intake data and the expanded National Heart, Lung and Blood Institute food composition data base, these analyses of sources of variance have been expanded to include classes of carbohydrate, vitamin A, vitamin C, thiamin, riboflavin, niacin, calcium, iron, total ash, caffeine, and crude fiber. The analyses relate to observed intakes (replicated six times) of 30 adult males and 30 adult females obtained under a paired Graeco-Latin square design with sequence of interview, interviewer, and day of the week as determinants. Neither sequence nor interviewer made consistent contribution to variance. In females, day of the week had a significant effect for several nutrients. The major partitioning of variance was between interindividual variation (between subjects) and intraindividual variation (within subjects) which included both true day-to-day variation in intake and methodological variation. For all except caffeine, the intraindividual variability of 1-day data was larger than the interindividual variability. For vitamin A, almost all of the variance was associated with day-to-day variability. One day data provide a very inadequate estimate of usual intake of individuals. In the design of nutrition studies it is critical that the intended use of dietary data be a major consideration in deciding on methodology. There is no ideal dietary method. There may be preferred methods for particular purposes.
Philippe Rocca-Serra
graeco latin square design
only 2 articles in pubmed ->probably irrelevant
hyper graeco latin square design
Adapted from: http://www.itl.nist.gov/div898/handbook/pri/section3/pri3321.htm and
PRS to do
Philippe Rocca-Serra
hyper graeco latin square design
no example found in pubmed->not in use in the community
replicate design
A replicate experimental design type is where a series of replicates are performed to evaluate reproducibility or as a pilot study to determine the appropriate number of replicates for a subsequent experiments.
MO_885
Philippe Rocca-Serra on behalf of MO
replicate design
time series design
Groups of assays that are related as part of a time series.
MO_887
PMID: 14744830-Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, agricultural and pharmaceutical sciences. There are myriad sources of uncertainty in microarray experiments, and rigorous experimental design is essential for fully realizing the potential of these valuable resources. Two questions frequently asked by biologists on the brink of conducting cDNA or two-colour, spotted microarray experiments are 'Which mRNA samples should be competitively hybridized together on the same slide?' and 'How many times should each slide be replicated?' Early experience has shown that whilst the field of classical experimental design has much to offer this emerging multi-disciplinary area, new approaches which accommodate features specific to the microarray context are needed. In this paper, we propose optimal designs for factorial and time course experiments, which are special designs arising quite frequently in microarray experimentation. Our criterion for optimality is statistical efficiency based on a new notion of admissible designs; our approach enables efficient designs to be selected subject to the information available on the effects of most interest to biologists, the number of arrays available for the experiment, and other resource or practical constraints, including limitations on the amount of mRNA probe. We show that our designs are superior to both the popular reference designs, which are highly inefficient, and to designs incorporating all possible direct pairwise comparisons. Moreover, our proposed designs represent a substantial practical improvement over classical experimental designs which work in terms of standard interactions and main effects. The latter do not provide a basis for meaningful inference on the effects of most interest to biologists, nor make the most efficient use of valuable and limited resources.
Philippe Rocca-Serra on behalf of MO
time series design
group assignment
cohort assignment
study assignment
Assigning' to be treated with active ingredient role' to an organism during group assignment. The group is those organisms that have the same role in the context of an investigation
OBI Plan
Philippe Rocca-Serra
group assignment
group assignment is a process which has an organism as specified input and during which a role is assigned
genetic transformation
OBI branch derived
PERSON:Kevin Clancy
The transduction of E. coli through the introduction of a plasmid encoding for M. avium p35
genetic modification
genetic transformation
the introduction. alteration or integration of genetic material into a cell or organism
age
A time quality inhering in a bearer by virtue of how long the bearer has existed.
age
length
length
A 1-D extent quality which is equal to the distance between two points.
behavioral quality
An organismal quality inhering in a bearer by virtue of the bearer's behavior aggregate of the responses or reactions or movements in a given situation.
behavioral quality
quality of a single physical entity
A physical object quality which inheres in a single-bearer.
quality of a single physical entity
handedness
A behavioral quality inhering ina bearer by virtue of the bearer's unequal distribution of fine motor skill between its left and right hands or feet.
handedness
left handedness
Handedness where the organism preferentially uses the left hand or foot for tasks requiring the use of a single hand or foot or a dominant hand or foot.
left handedness
right handedness
Handedness where the organism preferentially uses the right hand or foot for tasks requiring the use of a single hand or foot or a dominant hand or foot.
right handedness
ambidextrous handedness
Handedness where the organism exhibits no overall dominance in the use of right or left hand or foot in the performance of tasks that require one hand or foot or a dominant hand or foot.
ambidextrous handedness
region
A sequence_feature with an extent greater than zero. A nucleotide region is composed of bases and a polypeptide region is composed of amino acids.
primary structure of sequence macromolecule
region
sequence
length unit
A unit which is a standard measure of the distance between two points.
length unit
time unit
A unit which is a standard measure of the dimension in which events occur in sequence.
time unit
temperature unit
A unit which is a standard measure of the average kinetic energy of the particles in a sample of matter.
temperature unit
concentration unit
A unit which represents a standard measurement of how much of a given substance there is mixed with another substance.
concentration unit
data collection by censoring
Jie Zheng, Oliver He
a data collection by sampling process that results in a collection of data generated from an censoring.
example to be eventually removed
example to be eventually removed
failed exploratory term
Person:Alan Ruttenberg
The term was used used in an attempt to structure part of the ontology but in retrospect failed to do a good job
failed exploratory term
metadata complete
Class has all its metadata, but is either not guaranteed to be in its final location in the asserted IS_A hierarchy or refers to another class that is not complete.
metadata complete
organizational term
PERSON:Alan Ruttenberg
organizational term
term created to ease viewing/sort terms for development purpose, and will not be included in a release
ready for release
Class has undergone final review, is ready for use, and will be included in the next release. Any class lacking "ready_for_release" should be considered likely to change place in hierarchy, have its definition refined, or be obsoleted in the next release. Those classes deemed "ready_for_release" will also derived from a chain of ancestor classes that are also "ready_for_release."
ready for release
metadata incomplete
Class is being worked on; however, the metadata (including definition) are not complete or sufficiently clear to the branch editors.
metadata incomplete
uncurated
Nothing done yet beyond assigning a unique class ID and proposing a preferred term.
uncurated
pending final vetting
All definitions, placement in the asserted IS_A hierarchy and required minimal metadata are complete. The class is awaiting a final review by someone other than the term editor.
pending final vetting
core
Core is an instance of a grouping of terms from an ontology or ontologies. It is used by the ontology to identify main classes.
PERSON: Alan Ruttenberg
PERSON: Melanie Courtot
core
placeholder removed
placeholder removed
terms merged
An editor note should explain what were the merged terms and the reason for the merge.
terms merged
term imported
This is to be used when the original term has been replaced by a term imported from an other ontology. An editor note should indicate what is the URI of the new term to use.
term imported
term split
This is to be used when a term has been split in two or more new terms. An editor note should indicate the reason for the split and indicate the URIs of the new terms created.
term split
universal
A Formal Theory of Substances, Qualities, and Universals, http://ontology.buffalo.edu/bfo/SQU.pdf
Alan Ruttenberg
Hard to give a definition for. Intuitively a "natural kind" rather than a collection of any old things, which a class is able to be, formally. At the meta level, universals are defined as positives, are disjoint with their siblings, have single asserted parents.
universal
defined class
"definitions", in some readings, always are given by necessary and sufficient conditions. So one must be careful (and this is difficult sometimes) to distinguish between defined classes and universal.
A defined class is a class that is defined by a set of logically necessary and sufficient conditions but is not a universal
Alan Ruttenberg
defined class
named class expression
A named class expression is a logical expression that is given a name. The name can be used in place of the expression.
Alan Ruttenberg
named class expression
named class expressions are used in order to have more concise logical definition but their extensions may not be interesting classes on their own. In languages such as OWL, with no provisions for macros, these show up as actuall classes. Tools may with to not show them as such, and to replace uses of the macros with their expansions
to be replaced with external ontology term
Alan Ruttenberg
Terms with this status should eventually replaced with a term from another ontology.
group:OBI
to be replaced with external ontology term
requires discussion
A term that is metadata complete, has been reviewed, and problems have been identified that require discussion before release. Such a term requires editor note(s) to identify the outstanding issues.
Alan Ruttenberg
group:OBI
requires discussion
right handed
right handed
ambidexterous
ambidexterous
left handed
left handed
Edingburgh handedness inventory
Edingburgh handedness inventory
PERSON:Alan Ruttenberg
PERSON:Jessica Turner
PMID:5146491#Oldfield, R.C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9, 97-113
WEB:http://www.cse.yorku.ca/course_archive/2006-07/W/4441/EdinburghInventory.html
The Edinburgh Handedness Inventory is a set of questions used to assess the dominance of a person's right or left hand in everyday activities.
concentration unit
A unit which represents a standard measurement of how much of a given substance there is mixed with another substance.
concentration unit