1. From GENIA to BioTop – Towards a Top-Level Ontology for Biology Stefan Schulz, Elena Beisswanger, Udo Hahn, Joachim Wermter, Anand Kumar, Holger Stenzhorn Freiburg University, Jena University, Saarland University Germany

2. Need for Ontologies in Biology Raw Data Experimental Data

3. Need for Ontologies in Biology MEDLINE Literature Collection Raw Data Experimental Data

4. Need for Ontologies in Biology Yeast UniProt MEDLINE Literature Collection FlyBase MouseRaw Data Experimental Data Databases

5. Need for Ontologies in Biology Yeast UniProt MEDLINE Literature Collection FlyBase MouseRaw Data Experimental Data Databases Ontologies

6. OBO (Open Biomedical Ontologies) About 60 ‘ontologies’ -Gene Ontology (GO) -Sequence Ontology (SO) -Cell Ontology (CO) -Chemical entities of biological interest (ChEBI) -Anatomy of model organisms -… and others Ontologies unconnected, upper level missing OBO foundry project -Standards for bio-medical ontology development -Ontology integration Flood of Semi-Formal Bio-Ontologies

7. Ontological Layers Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology

8. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) Ontological Layers

9. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) Ontological Layers Transcription DNA-dependent transcription antisense RNA transcription mRNA transcription rRNA transcription tRNA transcription … (from Gene Ontology)

10. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) DOLCE BFO Ontological Layers

11. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) DOLCE BFO Ontological Layers Entity Continuant Dependent Continuant Realizable Entity Function Role Independent Continuant Object Object Aggregate Occurrent (from BFO)

12. Domain Upper Ontology / Top Domain Ontology Upper Ontology / Top Ontology Domain Ontology OBO (GO, SO, ChEBI, …) DOLCE BFO Ontological Layers

13. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) DOLCE BFO Ontological Layers

14. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) DOLCE BFO Ontological Layers Biology Domain: Organism Body Part Cell Cell Component Tissue Protein Nucleic Acid DNA RNA Biological Function Biological Process

15. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) Simple Bio Upper Ontology GFO-Bio DOLCE BFO Ontological Layers GENIA

16. Upper Ontology / Top Ontology Domain Upper Ontology / Top Domain Ontology Domain Ontology OBO (GO, SO, ChEBI, …) Simple Bio Upper Ontology GFO-Bio GENIA DOLCE BFO Ontological Layers BioTop

17. Developed at Tsujii Laboratory, University Tokyo Taxonomy, 48 classes Verbal definitions (“scope notes”) Purpose: Semantic annotation of biological papers “The GENIA ontology is intended to be a formal model of cell signaling reactions in human. It is to be used as a basis of thesauri and semantic dictionaries for natural language processing applications […] Another use of the GENIA ontology is to provide a basis for integrated view of multiple databases” GENIA Ontology

18. Annotation of Biological Entities We have shown that interleukin-1 (IL-1) and IL-2 control IL-2 receptor alpha (IL-2R alpha) gene transcription in CD4-CD8- murine T- lymphocyte precursors. Here we map the cis- acting elements that mediate interleukin responsiveness of the mouse IL-2R alpha gene using a thymic lymphoma-derived hybridoma (PC60). The transcriptional response of the IL-2R alpha gene to stimulation by IL-1 + IL-2 is biphasic. IL-1 induces a rapid, protein synthesis-independent appearance of IL-2R alpha mRNA that is blocked by inhibitors of NF-kappa B activation.

19. Annotation of Biological Entities We have shown that interleukin-1 (IL-1) and IL-2 control IL-2 receptor alpha (IL-2R alpha) gene transcription in CD4-CD8- murine T- lymphocyte precursors. Here we map the cis- acting elements that mediate interleukin responsiveness of the mouse IL-2R alpha gene using a thymic lymphoma-derived hybridoma (PC60). The transcriptional response of the IL-2R alpha gene to stimulation by IL-1 + IL-2 is biphasic. IL-1 induces a rapid, protein synthesis-independent appearance of IL-2R alpha mRNA that is blocked by inhibitors of NF-kappa B activation.

20. Annotation of Biological Entities We have shown that interleukin-1 (IL-1) and IL-2 control IL-2 receptor alpha (IL-2R alpha) gene transcription in CD4-CD8- murine T- lymphocyte precursors. Here we map the cis- acting elements that mediate interleukin responsiveness of the mouse IL-2R alpha gene using a thymic lymphoma-derived hybridoma (PC60). The transcriptional response of the IL-2R alpha gene to stimulation by IL-1 + IL-2 is biphasic. IL-1 induces a rapid, protein synthesis-independent appearance of IL-2R alpha mRNA that is blocked by inhibitors of NF-kappa B activation.

21. Annotation of Biological Entities We have shown that interleukin-1 (IL-1) and IL-2 control IL-2 receptor alpha (IL-2R alpha) gene transcription in CD4-CD8- murine T- lymphocyte precursors. Here we map the cis- acting elements that mediate interleukin responsiveness of the mouse IL-2R alpha gene using a thymic lymphoma-derived hybridoma (PC60). The transcriptional response of the IL-2R alpha gene to stimulation by IL-1 + IL-2 is biphasic. IL-1 induces a rapid, protein synthesis-independent appearance of IL-2R alpha mRNA that is blocked by inhibitors of NF-kappa B activation.

22. http://www-tsujii.is.s.u-tokyo.ac.jp/~genia/ corpus/GENIAontology.owl GENIA Ontology

23. Amino Acid Monomer: “An amino acid monomer, e.g. tyrosine, serine, tyr, ser” DNA: “DNAs include DNA groups, families, molecules, domains, and regions” GENIA Scope Notes

24. False Ontological Parent GENIA: Source ‘Organism’, ‘Tissue’, … are objects and not primarily sources! ‘Source’ is a role … “Sources are biological locations where substances are found …”

25. Are the instances of ‘Cell Type’ classes ? Otherwise rename the class as ‘Cell’! Misconception of Type GENIA: Cell Type “A cell type, e.g. T- Lymphocyte, T-cell, astrocyte, fibroblast”

26. Non-Conformant Naming Policy GENIA: Amino Acid, GENIA: Protein “An amino acid molecule or the compounds that consist of amino acids.” “Proteins include protein groups, families, molecules, complexes, and substructures.” Names suggest single molecules Don’t work against biologists’ intuition!

27. Top level ontology for biology Ontologically founded Formal semantics Use in bio text mining BioTop

28. foundational spatial temporal participation OBO Relations Ontology

29. foundational spatial temporal participation OBO Relations Ontology BioTop Relations

30. partOf properPartOf locatedIn derivesFrom hasParticipant

31. BioTop Relations partOf properPartOf locatedIn derivesFrom hasParticipant hasFunction (functionOf)

32. BioTop Relations grainOf (hasGrain) componentOf (hasComponent) partOf properPartOf locatedIn derivesFrom hasParticipant hasFunction (functionOf)

33. hasComponent non-transitive subrelation of hasPart Example: Definition of Protein Compounds are determined by their components Compound hasComponent Protein Arginine Carbon Oxygen NH 2

34. hasGrain non-transitive subrelation of hasPart Example: “Collective of Cell hasGrain only Cell” Collectives can gain or lose grains without changing their identity Collective hasGrain

35. Classes defined by necessary and sufficient conditions Rationales -Precise understanding of meaning -Empowering the classifier for automated validation processes Required introduction of new classes, e.g. Phosphate, Ribose Full Definitions Necessary conditions of class ‘Nucleotide’ Nucleotide Ribose Base Phosphate

36. Rearranged Classes GENIABioTop hasComponent componentOf properPartOf

37. BioTop.owl : -143 non-taxonomic relation instances (seven relation types) -128 classes BioTopGenia.owl : -Imports GENIA -Links BioTop classes to GENIA classes (if possible) BioTop Results

38. Ontology Integration Biological Process↔ Biological Process Gene Ontology Protein Function ↔ Molecular Function Gene Ontology Cell Component ↔ Cellular Component Gene Ontology Cell ↔ Cell Cell Ontology and Cell FMA Atom↔ Atoms ChEBI Organic Compound↔ Organic Molecular Entities ChEBI Tissue ↔ Tissue FMA DNA, RNA↔ DNA Sequence Ontology, RNA Sequence Ontology Protein↔ Protein Sequence Ontology BioTopOBO Ontologies

39. Conclusions GENIA Ontology as de facto standard for bio text mining but with major shortcomings BioTop as a new proposal for an upper-level ontology for biology -principled -formalized -enhanced Coupling to OBO ontologies

40. BioTop: www.ifomis.org/biotop Current Projects on Bio Text Mining at Jena University: BOOTStrep: www.bootstrep.eu Bootstrapping ontologies and terminologies StemNet: www.stemnet.de A knowledge management system for stem cell biology

41. hasGrain non-transitive subrelation of hasPart “Collective of x hasGrain x” Collectives do not depend on single elements Controversial: Referents in biological texts: Collectives (pluralities) or count objects? “Emerin is phosphorylated on serine 49 by protein kinase A” Collectives and Relation hasGrain PKA or Emerin