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Integrating genomic knowledge sources through an anatomy ontology

Integrating genomic knowledge sources through an anatomy ontology. Gennari JH, Silberfein A, and Wiley JC Pac Symp Biocomputing 2005: 115-26 Presented by Morgan Langille MEDG 505. Pac Symp Biocomputing?. Proceedings of the Pacific Symposium on Biocomputing

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Integrating genomic knowledge sources through an anatomy ontology

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  1. Integrating genomic knowledge sources through an anatomy ontology Gennari JH, Silberfein A, and Wiley JC Pac Symp Biocomputing 2005: 115-26 Presented by Morgan Langille MEDG 505

  2. Pac Symp Biocomputing? • Proceedings of the Pacific Symposium on Biocomputing • “… research in the theory and application of computational methods in problems of biological significance” • Jan, 2005 @ Hawaii Morgan Langille

  3. Outline Integrated Knowledge Base! Gene Ontology Gene Expression Data Foundational Model of Anatomy Morgan Langille

  4. Foundational Model of Anatomy (FMA) • FMA describes all of human anatomy (even sub-cellular) as a symbolic ontology of concepts and relationships • Designed for the genomics domain not for a certain type of user • Can be navigated by humans and machines • No function or physiology of anatomy Morgan Langille

  5. Foundational Model of Anatomy (FMA) • Implemented using Protégé • Protégé • Authoring and editing environment for ontologies • Can be used to view the FMA • Freely accessible since 2003 • Can be viewed in a web browser Morgan Langille

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  7. Gene Ontology • Gene Ontology (GO) is a controlled vocabulary that can be used to annotate genes • Includes databases such as: • FlyBase (Drosophila) • Saccharomyces Genome Database (SGD) • Mouse Genome Database (MGD) • WormBase • Rat Genome Database (RGD) Morgan Langille

  8. Gene Ontology • The three organizing principles of GO: • molecular function - catalytic activity, transporter activity, or binding, etc. • biological process - cell growth and maintenance or signal transduction, etc. • cellular component - rough endoplasmic reticulum or nucleus, ribosome, proteasome, etc. • No tissue specific information Morgan Langille

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  10. Integrating GO and FMA • Connect GO with FMA via cellular structure • Hand built connections of 150 terms between FMA and GO • Built Protégé plugin to view the integrated data Morgan Langille

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  12. Gene Expression Data • No standard source for anatomic knowledge for annotation of gene expression results • Standards and Ontologies for Functional Genomics (SOFG) • Focused on integrating ontologies for mouse and human anatomies • Devoloped “SOFG anatomy entry list” (SAEL) • SAEL – 100 anatomic terms • Can be used to annotate gene expression data Morgan Langille

  13. Integrating Gene Expression Data • Integrate the gene expression data from the Mouse Genome Database (MGD) • Built connections between anatomy terms used in MGD to concepts defined in FMA • Focused only on brain regions • Few anatomic differences between human and mouse brain regions Morgan Langille

  14. Overview of MGD, GO, and FMA data integration Morgan Langille

  15. Example Morgan Langille

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  17. Future Work/Problems • Automation of connecting ontologies • Prompt • Plugin for Protégé • Semi-automatic merging of ontologies • BioMediator • Dynamic connections • Anatomies will not always map between species Morgan Langille

  18. Conclusions • Many ontologies already exist in biology such as GO and the FMA • Integration of multiple sources can be based on anatomy • Future work is needed in automating production of ontology connections Morgan Langille

  19. Questions? • Is anatomy the best knowledge hub? Morgan Langille

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