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What is an ontology and Why should you care? Barry Smith ontology.buffalo/smith

What is an ontology and Why should you care? Barry Smith http://ontology.buffalo.edu/smith with thanks to Jane Lomax, Gene Ontology Consortium. You’re interested in which genes control heart muscle development 17,536 results. time. Defense response Immune response Response to stimulus

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What is an ontology and Why should you care? Barry Smith ontology.buffalo/smith

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  1. What is an ontology and Why should you care? Barry Smith http://ontology.buffalo.edu/smith with thanks to Jane Lomax, Gene Ontology Consortium

  2. You’re interested in which genes control heart muscle development 17,536 results

  3. time Defense response Immune response Response to stimulus Toll regulated genes JAK-STAT regulated genes Puparial adhesion Molting cycle hemocyanin Amino acid catabolism Lipid metobolism Peptidase activity Protein catabloism Immune response Immune response Toll regulated genes control attacked Microarray data shows changed expression of thousands of genes. How will you spot the patterns?

  4. Ontologies provide a way to capture and represent all this knowledge in a computable form

  5. Uses of ‘ontology’ in PubMed abstracts

  6. By far the most successful: The Gene Ontology

  7. Definitions

  8. Gene products involved in cardiac muscle development in humans

  9. Term Search Results

  10. Hierarchical view representing relations between represented types

  11. How GO can be used to help analyse microarray data • Treat samples • Collect mRNA • Label • Hybridize • Scan • Normalize • Select differentially regulated genes • Understand the biological phenomena involved

  12. Gene 1 Apoptosis Cell-cell signaling Protein phosphorylation Mitosis … Gene 2 Growth control Mitosis Oncogenesis Protein phosphorylation … Gene 3 Growth control Mitosis Oncogenesis Protein phosphorylation … Gene 4 Nervous system Pregnancy Oncogenesis Mitosis … Gene 100 Positive control. of cell proliferation Mitosis Oncogenesis Glucose transport … Traditional analysis operates via literature search for each successive gene

  13. GO:0006915 : apoptosis But by using GO annotations, this work has already been done

  14. GO allows grouping by process Mitosis Gene 2 Gene 5 Gene45 Gene 7 Gene 35 … Glucose transport Gene 7 Gene 3 Gene 6 … Apoptosis Gene 1 Gene 53 Growth Gene 5 Gene 2 Gene 6 … Positive control. of cell proliferation Gene 7 Gene 3 Gene 12 … Allows us to ask meaningful questions of microarray data e.g. which genes are involved in the same process, with same/different expression patterns?

  15. How does the Gene Ontology work?

  16. 1. It provides a controlled vocabulary contributing to the cumulativity of scientific results achieved by distinct research communities (if we all use kilograms, meters, seconds … , our results are callibrated)

  17. 2. It provides a tool for algorithmic reasoning

  18. Hierarchical view representing relations between represented types

  19. The massive quantities of annotations to gene products in terms of the GO allows a new kind of research

  20. Uses of GO in studies of • pathways associated with heart failure development correlated with cardiac remodeling (PMID 18780759) • sex-specific pathways in early cardiac response to pressure overload in mice (PMID 18665344) • molecular signature of cardiomyocyte clusters derived from human embryonic stem cells (PMID 18436862) • contrast between cardiac left ventricle and diaphragm muscle in expression of genes involved in carbohydrate and lipid metabolism. (PMID 18207466 ) • immune system involvement in abdominal aortic aneurisms in humans (PMID 17634102) • …

  21. But GO covers only three sorts of biological entities • cellular components • molecular functions • biological processes and does not provide representations of disease-related phenomena

  22. How extend the GO to help integrate complex representations of reality help human beings find things in complex representations of reality help computers reason with complex representations of reality in other areas of biomedicine?

  23. The Open Biomedical Ontologies (OBO) Foundry

  24. RELATION TO TIME GRANULARITY initial OBO Foundry coverage

  25. CRITERIA • opennness • common formal language. • collaborative development • evidence-based maintenance • identifiers • versioning • textual and formal definitions CRITERIA

  26. CRITERIA • COMMON ARCHITECTURE: The ontology uses common formal relations • ORTHOGONALITY: One ontology for each domain

  27. LEADERSHIP • Michael Ashburner, Suzanna Lewis, Chris Mungall (GO Consortium) • Alan Ruttenberg (Science Commons, OWL Working Group, HCLS/Semantic Web) • Richard Scheuermann (ImmPort, CTSA) • Barry Smith

  28. OBO Foundry provides • tested guidelines enabling new groups to develop the ontologies they need in ways which counteract forking and dispersion of effort • an incremental bottoms-up approach to evidence-based terminology practices in medicine that is rooted in basic biology • automatic web-based linkage between medical terminologies and biological knowledge resources

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