A method for increasing expressivity of Gene Ontology annotations using a compositional approach
- Wellcome Trust Genome Campus, Hinxton, Cambridge (United Kingdom). European Molecular Biology Lab.-European Bioinformatics Inst. (EMBL-EBI)
- Univ. of Cambridge (United Kingdom). Cambridge Systems Biology Centre. Dept. of Biochemistry
- The Jackson Lab., Bar Harbor, ME (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division
- Univ. College London (United Kingdom). Inst. of Cardiovascular Science. Centre for Cardiovascular Genetics
- California Institute of Technology (CalTech), Pasadena, CA (United States). Division of Biology
Background: The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. Results: The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector–target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions. Conclusions: The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism’s gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1626296
- Journal Information:
- BMC Bioinformatics, Vol. 15, Issue 1; ISSN 1471-2105
- Publisher:
- BioMed CentralCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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