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Part III.The OBO Foundry Project:

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Title: Part III.The OBO Foundry Project:


1
Part III. The OBO Foundry Project
  • Towards Scientific Standards and
    Principles-Based Coordination in Biomedical
    Ontology Development

2
High quality shared ontologies build communities
  • NIH, FDA trend to consolidate ontology-based
    standards for the communication and processing of
    biomedical data.
  • caBIG / NECTAR / BIRN / BRIDG ...

3
  • http//obo.sourceforge.net

4
http//www.geneontology.org/
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8
The Methodology of Annotations
  • GO employs scientific curators, who use
    experimental observations reported in the
    biomedical literature to link gene products with
    GO terms in annotations.
  • This gene product exercises this function, in
    this part of the cell, leading to these
    biological processes

9
The Methodology of Annotations
  • This process of annotating literature leads to
    improvements and extensions of the ontology,
    which in turn leads to better annotations
  • This institutes a virtuous cycle of improvement
    in the quality and reach of both future
    annotations and the ontology itself.
  • Annotations ontology taken together yield a
    slowly growing computer-interpretable map of
    biological reality.

10
RECALL Alignment of GO and Cell ontologies will
permit the generation of consistent and complete
definitions
GO

Cell type

Osteoblast differentiation Processes whereby an
osteoprogenitor cell or a cranial neural crest
cell acquires the specialized features of an
osteoblast, a bone-forming cell which secretes
extracellular matrix.
New Definition
11
The OBO Foundry
12
  • A subset of OBO ontologies, whose developers
    have agreed in advance to accept a common set of
    principles designed to ensure
  • intelligibility to biologists (curators,
    annotators, users)
  • formal robustness
  • stability
  • compatibility
  • interoperability
  • support for logic-based reasoning

13
  • Custodians
  • Michael Ashburner (Cambridge)
  • Suzanna Lewis (Berkeley)
  • Barry Smith (Buffalo/Saarbrücken)

14
A collaborative experiment
  • participants have agreed in advance to a growing
    set of principles specifying best practices in
    ontology development
  • designed to guarantee interoperability of
    ontologies from the very start

15
  • The developers of each ontology commit to its
    maintenance in light of scientific advance, and
    to soliciting community feedback for its
    improvement.
  • They commit to working with other Foundry
    members to ensure that, for any particular
    domain, there is community convergence on a
    single reference ontology.

16
  • Initial Candidate Members of the OBO Foundry
  • GO Gene Ontology
  • CL Cell Ontology
  • SO Sequence Ontology
  • ChEBI Chemical Ontology
  • PATO Phenotype (Quality) Ontology
  • FuGO Functional Genomics Investigation Ontology
  • FMA Foundational Model of Anatomy
  • RO Relation Ontology 

17
  • Under development
  • Disease Ontology
  • Mammalian Phenotype Ontology
  • OBO-UBO / Ontology of Biomedical Reality
  • Organism (Species) Ontology
  • Plant Trait Ontology
  • Protein Ontology
  • RnaO RNA Ontology
  • NCI Thesaurus ????

18
  • Considered for development
  • Environment Ontology
  • Behavior Ontology
  • Biomedical Image Ontology
  • Clinical Trial Ontology

19
CRITERIA
The OBO Foundry
The ontology is open and available to be used by
all. The developers of the ontology agree in
advance to collaborate with developers of other
OBO Foundry ontology where domains overlap. The
ontology is in, or can be instantiated in, a
common formal language.
20
CRITERIA
  • The ontology possesses a unique identifier space
    within OBO.
  • The ontology provider has procedures for
    identifying distinct successive versions.
  • The ontology includes textual definitions for
    all terms.

21
CRITERIA
  • The ontology has a clearly specified and clearly
    delineated content.
  • The ontology is well-documented.
  • The ontology has a plurality of independent
    users.

22
CRITERIA
  • The ontology uses relations which are
    unambiguously defined following the pattern of
    definitions laid down in the OBO Relation
    Ontology.
  • Genome Biology 2005, 6R46

23
CRITERIA
The OBO Foundry
  • Further criteria will be added over time in
    order to bring about a gradual improvement in the
    quality of the ontologies in the Foundry

24
Goal
  • Alignment of OBO Foundry ontologies through a
    common system of formally defined relations
  • to enable reasoning both within and across
    ontologies

25
A reference ontology
  • is analogous to a scientific theory it seeks to
    optimize representational adequacy to its subject
    matter to the maximal degree that is compatible
    with the constraints of computational usefulness.

26
An application ontology
  • is comparable to an engineering artifact such as
    a software tool. It is constructed for a specific
    practical purpose.
  • Examples
  • National Cancer Institute Thesaurus
  • FuGO Functional Genomics Investigation
    Ontology

27
Reference Ontology vs. Application Ontology
  • Currently, application ontologies are often
    built afresh for each new task commonly
    introducing not only idiosyncrasies of format or
    logic, but also simplifications or distortions of
    their subject-matters.
  • To solve this problem application ontology
    development should take place always against the
    background of a formally robust reference
    ontology framework

28
Reference Ontologies promote re-usability of data
  • if dataschemas are formulated using terms drawn
    from a reference ontology used by others, then
    the data will be to this degree more accessible
    to others

29
Advantages of the methodology of shared
coherently defined ontologies
  • promotes quality assurance (better coding)
  • guarantees automatic reasoning across ontologies
    and across data at different granularities
  • makes links between ontologies explicit
  • yields direct connection to temporally indexed
    instance data

30
Advantages of the methodology of shared
coherently defined ontologies
  • We know that high-quality ontologies can help in
    creating better mappings e.g. between human and
    model organism phenotypes
  • S Zhang, O Bodenreider, Alignment of Multiple
    Ontologies of Anatomy Deriving Indirect Mappings
    from Direct Mappings to a Reference Ontology,
    AMIA 2005

31
Reference Ontologies
  • are already being used to create technology to
    aid literature search
  • http//www.gopubmed.org/

32
  • Goal
  • to create a family of gold standard reference
    ontologies upon which terminologies developed for
    specific applications can draw

33
  • Goal
  • to introduce the scientific method into ontology
    development
  • all Foundry ontologies must be constantly updated
    in light of scientific advance
  • all Foundry ontology developers must work with
    all other Foundry ontology developers in a spirit
    of scientific collaboration

34
  • Goal
  • to replace the current policy of ad hoc
    creation of new database schemas by each clinical
    research group by providing reference ontologies
    in terms of which database schemas can be defined

35
  • Goal
  • to introduce some of the features of scientific
    peer review into biomedical ontology development

36
  • Goal
  • to create controlled vocabularies for use by
    clinical trial banks, clinical guidelines bodies,
    scientific journals, ...

37
  • Goal
  • to create an evolving map-like representation of
    the entire domain of biological reality

38
GOs three ontologies
biological process
molecular function
cellular component
39
organism-level physiology
molecular process
cellular physiology
molecular function (GO)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
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41
organism-level physiology
cellular physiology
molecular process
normal (functionings)
molecular function (GO)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
42
pathophysiology (disease)
pathological (malfunctionings)
pathoanatomy (fly, fish, human ...)
43
pathophysiology (disease)
organism-level physiology
cellular physiology
molecular process
molecular function (GO)
pathoanatomy (fly, fish, human ...)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy (GO)
anatomy (fly, fish, human...)
44
pathophysiology (disease)
organism-level physiology
cellular physiology
molecular process
molecular function (GO)
phenotype
pathoanatomy (fly, fish, human ...)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
45
pathophysiology (disease)
organism-level physiology
cellular physiology
molecular process
molecular function (GO)
phenotype
pathoanatomy (fly, fish, human ...)
cell (types)
species
ChEBI, Sequence, RNA ...
cellular anatomy
anatomy (fly, fish, human...)
investigation (FuGO)
46
  • Judith Blake
  • The use of bio-ontologies ensures consistency
    of data curation, supports extensive data
    integration, and enables robust exchange of
    information between heterogeneous informatics
    systems. ..
  • ontologies formally define relationships
    between the concepts.

47
"Gene Ontology Tool for the Unification of
Biology"
  • an ontology "comprises a set of well-defined
    terms with well-defined relationships"
  • (Ashburner et al., 2000, p. 27)

48
Low Hanging Fruit
  • Ontologies should include only those relational
    assertions which hold universally ( have the
    ALL-SOME form)
  • Often, order will matter here
  • We can include
  • adult transformation_of child
  • but not
  • child transforms_into adult

49
The Gene Ontology
50
GOs three ontologies
molecular functions
biological processes
cellular components
51
When a gene is identified
  • three types of questions need to be addressed
  • 1. Where is it located in the cell?
  • 2. What functions does it have on the molecular
    level?
  • 3. To what biological processes do these
    functions contribute?

52
Three granularities
  • Cellular (for components)
  • Molecular (for functions)
  • Organ organism (for processes)

53
GO has cells
  • but it does not include terms for molecules or
    organisms within any of its three ontologies
  • except e.g. GO0018995 host
  • Def. Any organism in which another organism
    spends part or all of its life cycle

54
Are the relations between functions and processes
a matter of granularity?
  • Molecular activities are the building blocks of
    biological processes ?
  • But they are not allowed to be represented in GO
    as parts of biological processes

55
GOs three ontologies
biological processes
molecular functions
cellular components
56
  • What does function mean?
  • an entity has a biological function if and only
    if it is part of an organism and has a
    disposition to act reliably in such a way as to
    contribute to the organisms survival
  • the function is this disposition

57
Improved version
  • an entity has a biological function if and only
    if it is part of an organism and has a
    disposition to act reliably in such a way as to
    contribute to the organisms realization of the
    canonical life plan for an organism of that type

58
This canonical life plan might include
  • canonical embryological development
  • canonical growth
  • canonical reproduction
  • canonical aging
  • canonical death

59
The function of the heart is to pump blood
  • Not every activity (process) in an organism is
    the exercise of a function there are
  • mal functionings
  • side-effects (heart beating)
  • accidents (external interference)
  • background stochastic activity

60
Kidney
61
Nephron
62
Functional Segments
63
Functions
64
Functions
  • This is a screwdriver
  • This is a good screwdriver
  • This is a broken screwdriver
  • This is a heart
  • This is a healthy heart
  • This is an unhealthy heart

65
Functions are associated with certain
characteristic process shapes
  • Screwdriver rotates and simultaneously moves
    forward simultaneously transferring torque from
    hand and arm to screw
  • Heart performs a contracting movement inwards
    and an expanding movement outwards

66
Not functioning at all
  • leads to death, modulo
  • internal factors
  • plasticity
  • redundancy (2 kidneys)
  • criticality of the system involved
  • external factors
  • prosthesis (dialysis machines, oxygen tent)
  • special environments
  • assistance from other organisms

67
What clinical medicine is for
  • to eliminate malfunctioning by fixing broken
    body parts
  • (or to prevent the appearance of malfunctioning
    by intervening e.g. at the molecular level)

68
Hypothesis there are no bad functions
  • It is not the function of an oncogene to cause
    cancer
  • Oncogenes were in every case proto-oncogenes
    with functions of their own
  • They become oncogenes because of bad
    (non-prototypical) environments

69
Is there an exception for molecular functions?
  • Does this apply only to functions on biological
    levels of granularity
  • ( levels of granularity coarser than the
    molecule) ?
  • If pathology is the deviation from (normal)
    functioning, does it make sense to talk of a
    pathological molecule?
  • (Pathologically functioning molecule vs.
    pathologically structured molecule)

70
Is there an exception for molecular functions?
  • A molecular function is a propensity of a gene
    product instance to perform actions on the
    molecular level of granularity.
  • Hypothesis 1 these actions must be reliably
    such as to contribute to biological processes.
  • Hypothesis 2 these actions must be reliably
    such as to contribute to the organisms
    realization of the canonical life plan for an
    organism of that type.

71
The Gene Ontology
  • is a canonical ontology it represents only
    what is normal in the realm of molecular
    functioning

72
The GO is a canonical representation
  • The Gene Ontology is a computational
    representation of the ways in which gene products
    normally function in the biological realm
  • Nucl. Acids Res. 2006 34.

73
The FMA is a canonical representation
  • It is a computational representation of types
    and relations between types deduced from the
    qualitative observations of the normal human
    body, which have been refined and sanctioned by
    successive generations of anatomists and
    presented in textbooks and atlases of structural
    anatomy.

74
The importance of pathways (successive causality)
  • Each stage in the history of a disease
    presupposes the earlier stages
  • Therefore need to reason across time, tracking
    the order of events in time, using relations such
    as derives_from, transformation_of ...
  • Need pathway ontologies on every level of
    granularity

75
The importance of granularity (simultaneous
causality)
  • Networks are continuants
  • At any given time there are networks existing in
    the organism at different levels of granularity
  • Changes in one cause simultaneous changes in all
    the others
  • (Compare Boyles law a rise in temperature
    causes a simultaneous increase in pressure)

76
The Granularity Gulf
  • most existing data-sources are of fixed, single
    granularity
  • many (all?) clinical phenomena cross
    granularities
  • Therefore need to reason across time, tracking
    the order of events in time

77
Good ontologies require
  • consistent use of terms, supported by logically
    coherent (non-circular) definitions, in
    equivalent human-readable and computable formats
  • coherent shared treatment of relations to allow
    cascading inference both within and between
    ontologies

78
Three fundamental dichotomies
  • continuants vs. occurrents
  • dependent vs. independent
  • types vs. instances

79
ONTOLOGIES AREREPRESENTATIONS OF TYPESaka
kinds, universals, categories, species, genera,
...
80
  • Continuants (aka endurants)
  • have continuous existence in time
  • preserve their identity through change
  • exist in toto whenever they exist at all
  • Occurrents (aka processes)
  • have temporal parts
  • unfold themselves in successive phases
  • exist only in their phases

81
You are a continuant
  • Your life is an occurrent
  • You are 3-dimensional
  • Your life is 4-dimensional

82
Dependent entities
  • require independent continuants as their bearers
  • There is no run without a runner
  • There is no grin without a cat

83
Dependent vs. independent continuants
  • Independent continuants (organisms, cells,
    molecules, environments)
  • Dependent continuants (qualities, shapes, roles,
    propensities, functions)

84
All occurrents are dependent entities
  • They are dependent on those independent
    continuants which are their participants (agents,
    patients, media ...)

85
Top-Level Ontology
Continuant
Occurrent (always dependent on one or more
independent continuants)
Independent Continuant
Dependent Continuant
86
A representation of top-level types
Continuant
Occurrent
biological process
Independent Continuant
Dependent Continuant
cell component
molecular function
87
Top-Level Ontology
Continuant
Occurrent
Independent Continuant
Dependent Continuant
Side-Effect, Stochastic Process, ...
Functioning
Function
88
Top-Level Ontology
Continuant
Occurrent
Independent Continuant
Dependent Continuant
Functioning
Side-Effect, Stochastic Process, ...
Function
89
Top-Level Ontology
instances (in space and time)
90
Smith B, Ceusters W, Kumar A, Rosse C. On
Carcinomas and Other Pathological Entities, Comp
Functional Genomics, Apr. 2006
91
everything here is an independent continuant
92
Functions, etc.Some dependent continuants are
realizable
  • expression of a gene
  • application of a therapy
  • course of a disease
  • execution of an algorithm
  • realization of a protocol

93
Functions vs Functionings
  • the function of your heart to pump blood in
    your body
  • this function is realized in processes of
    pumping blood
  • not all functions are realized (consider the
    function of this sperm ...)

94
Concepts
  • Biomedical ontology integration will never be
    achieved through integration of meanings or
    concepts
  • The problem is precisely that different user
    communities use different concepts
  • Concepts are in your head and will change as your
    understanding changes
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