UniProt is a large life sciences database that uses several ontologies like the Gene Ontology, keywords, taxonomy, and pathways to provide consistent navigation and aggregation of its data on protein sequences, functions, and features. The document discusses how ontologies help organize UniProt's large amount of data and provide benefits like auto-completion, set-oriented views, and potential for automation. It also seeks feedback on which additional data from UniProt could be organized through more detailed ontologies.

1. UniProt & Ontologies How ontologies are used in the context of a large life sciences database Eric Jain Swiss Institute of Bioinformatics, Geneva April 2007

2. What is UniProt?

3. + +

4. UniMES UniRef UniParc ... UniProtKB

5. UniParc 8.9M sequences

6. 50% 1.5M 90% 2.9M 100% 4.5M UniRef 8.9M clusters

7. UniProtKB 4.5M entries reviewed 0.3M Species & organelles Description of function etc Keywords & GO Description of sequence features Sequence(s) Literature Citations Cross-References Protein & gene names

8. What is an Ontology?

9. unique identifier names and synonyms relationships within the ontology stable! mapped to other ontologies human-readable definitions machine-readable definitions

10. Why?

11. Practical. Navigation, auto-completion etc

13. Consistency! More than one way to say one thing...

14. Aggregate. i.e. set-oriented views

15. Automate?

16. What

17. Keywords Taxonomy Enzyme Pathways Tissues Subcellular Locations Cellular Components Gene Ontology

24. Summary Increased use of ontologies is inevitable as data volumes grow. UniProt has (or is in the process of introducing) several ontologies. What data will be "ontologized" and how detailed the ontologies are depends on your feedback ! [email_address]

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