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...

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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.

RECALL: Alignment of GO and Cell ontologies will permit the generation of consistent and complete definitions id: CL: name: osteoblast def: "A bone-forming cell which secretes an extracellular matrix. Hydroxyapatite crystals are then deposited into the matrix to form bone." [MESH:A ] is_a: CL: relationship: develops_from CL: relationship: develops_from CL: GO Cell type New Definition + = 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.

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 The OBO Foundry

13 Custodians Michael Ashburner (Cambridge) Suzanna Lewis (Berkeley) Barry Smith (Buffalo/Saarbrücken) The OBO Foundry

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 The OBO Foundry

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. The OBO Foundry

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 The OBO Foundry

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 ???? The OBO Foundry

18 Considered for development Environment Ontology Behavior Ontology Biomedical Image Ontology Clinical Trial Ontology The OBO Foundry

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 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. CRITERIA The OBO Foundry

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

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

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

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

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. The OBO Foundry

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 The OBO Foundry

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 The OBO Foundry

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 The OBO Foundry

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 The OBO Foundry

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 The OBO Foundry

31 Reference Ontologies are already being used to create technology to aid literature search The OBO Foundry

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

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 The OBO Foundry

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 The OBO Foundry

35 Goal: to introduce some of the features of scientific peer review into biomedical ontology development The OBO Foundry

36 Goal: to create controlled vocabularies for use by clinical trial banks, clinical guidelines bodies, scientific journals,... The OBO Foundry

37 Goal: to create an evolving map-like representation of the entire domain of biological reality The OBO Foundry

GO’s three ontologies molecular function cellular component biological process

cell (types) molecular function (GO) species molecular process cellular anatomy anatomy (fly, fish, human...) cellular physiology organism-level physiology ChEBI, Sequence, RNA...

cell (types) molecular function (GO) species molecular process cellular anatomy anatomy (fly, fish, human...) cellular physiology organism-level physiology ChEBI, Sequence, RNA... granular levels

cell (types) molecula r function (GO) species molecula r process cellular anatomy anatomy (fly, fish, human...) cellular physiology organism-level physiology ChEBI, Sequence, RNA... normal (functionings)

pathophysiology (disease) pathoanatomy (fly, fish, human...) pathological (malfunctionings)

cell (types) molecula r function (GO) species molecula r process cellular anatomy (GO) anatomy (fly, fish, human...) cellular physiology organism-level physiology ChEBI, Sequence, RNA... pathophysiology (disease) pathoanatomy (fly, fish, human...)

cell (types) molecula r function (GO) species molecula r process cellular anatomy anatomy (fly, fish, human...) cellular physiology organism-level physiology ChEBI, Sequence, RNA... pathophysiology (disease) pathoanatomy (fly, fish, human...) phenotype

cell (types) molecula r function (GO) species molecula r process cellular anatomy anatomy (fly, fish, human...) cellular physiology organism-level physiology ChEBI, Sequence, RNA... pathophysiology (disease) pathoanatomy (fly, fish, human...) phenotype 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 GO’s three ontologies molecular functions cellular components biological processes

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. GO: 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 GO’s three ontologies molecular functions cellular components biological processes

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 organism’s 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 organism’s 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 organism’s 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 Boyle’s 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 ARE REPRESENTATIONS OF TYPES aka 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...)

Top-Level Ontology Continuant Occurrent (always dependent on one or more independent continuants) Independent Continuant Dependent Continuant

= A representation of top-level types Continuant Occurrent Independent Continuant Dependent Continuant cell component biological process molecular function

Top-Level Ontology Continuant Occurrent Independent Continuant Dependent Continuant Functioning Side-Effect, Stochastic Process,... Function

Top-Level Ontology Continuant Occurrent Independent Continuant Dependent Continuant Functioning Side-Effect, Stochastic Process,... Function

Top-Level Ontology Continuant Occurrent Independent Continuant Dependent Continuant Quality Function Spatial Region Functioning Side-Effect, Stochastic Process,... 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