2

3 where in the body ? where in the cell ?

where in the body ? where in the cell ? what kind of organism ?

where in the body ? where in the cell ? what kind of organism ? what kind of disease process ?

to yield: distributed accessibility of the data to humans reasoning with the data cumulation for purposes of research incrementality and evolvability integration with clinical data Creating broad-coverage semantic annotation systems for biomedicine

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8

9 Gene Ontology a controlled structured vocabulary for annotation of gene product data

The OBO Foundry Idea MouseEcotope GlyProt DiabetInGene GluChem sphingolipid transporter activity

The OBO Foundry Idea MouseEcotope GlyProt DiabetInGene GluChem Holliday junction helicase complex

Sjöblöm et al. analyzed 13,023 genes in 11 breast and 11 colorectal cancers identified189 as being mutated at significant frequency and thus as providing targets for diagnostic and therapeutic intervention. correlations between functional information captured by GO for given gene product types and the expression patterns detected experimentally in selected instances of these types can help to elucidate underlying pathologies Sjöblöm T, et al. Science Oct 13;314(5797):

13 Five bangs for your GO buck 1.based in biological science 2.incremental approach (low hanging fruit) 3.cross-species data comparability (human, mouse, yeast, fly...) 4.cross-granularity data integration (molecule, cell, organ, organism) 5.cumulation of scientific knowledge in algorithmically tractable form which links people to software

14 what cellular component? what molecular function? what biological process?

a family of interoperable biomedical reference ontologies built around the Gene Ontology at its core and using the same principles a modular annotation catalogue of English phrases each module created by experts from the corresponding scientific community The OBO Foundry

RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) The OBO Foundry building out from the original GO

Karen Eilbecksong.sf.net properties and features of nucleic sequences Sequence Ontology (SO) RNA Ontology Consortium(under development) three-dimensional RNA structures RNA Ontology (RnaO) Barry Smith, Chris Mungallobo.sf.net/relationshiprelations Relation Ontology (RO) Protein Ontology Consortium(under development) protein types and modifications Protein Ontology (PrO) Michael Ashburner, Suzanna Lewis, Georgios Gkoutos obo.sourceforge.net/cgi -bin/ detail.cgi? attribute_and_value qualities of biomedical entities Phenotypic Quality Ontology (PaTO) Gene Ontology Consortiumwww.geneontology.org cellular components, molecular functions, biological processes Gene Ontology (GO) FuGO Working Groupfugo.sf.net design, protocol, data instrumentation, and analysis Functional Genomics Investigation Ontology (FuGO) JLV Mejino Jr., Cornelius Rosse fma.biostr.washington. edu structure of the human body Foundational Model of Anatomy (FMA) Melissa Haendel, Terry Hayamizu, Cornelius Rosse, David Sutherland, (under development) anatomical structures in human and model organisms Common Anatomy Refer- ence Ontology (CARO) Paula Dematos, Rafael Alcantara ebi.ac.uk/chebimolecular entities Chemical Entities of Bio- logical Interest (ChEBI) Jonathan Bard, Michael Ashburner, Oliver Hofman obo.sourceforge.net/cgi- bin/detail.cgi?cell cell types from prokaryotes to mammals Cell Ontology (CL) CustodiansURLScopeOntology

Ontologies being built to satisfy Foundry principles ab initio Clinical Trial Ontology (CIO) Common Anatomy Reference Ontology (CARO, DB1 & DB2) Mosquito Anatomy Ontology (MAO) Ontology for Biomedical Investigations (OBI) Phenotypic Quality Ontology (PATO, DB1 & DB2) Protein Ontology (PRO) Relation Ontology (RO) RNA Ontology (RnaO)

19 Draft Ontology for Multiple Sclerosis

Entry point for creation of web- accessible biomedical data GO initially low-tech to encourage users Simple (web-service-based) tools created to support the work of biologists in creating annotations (data entry) OBO  OWL DL converters now making OBO Foundry annotated data immediately accessible to Semantic Web data integration projects

GO allows distributed web-based collaboration the methodology gradually being evolved as service -based architecture by US National Center for Biomedical Ontology ( companies vs. cross-border collaboration

22 what cellular component? what molecular function? what biological process?

compare: legends for maps

compare: legends for maps common legends allow (cross-border) integration

25 legends for chemistry diagrams

26 MIAKT system legends for images

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ontologies as legends for data