title: A method for increasing expressivity of Gene Ontology annotations using a compositional approach.
abstract: 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.
authors.forename: Rachael P
authors.initials: RP
authors.lastname: Huntley
authors.forename: Midori A
authors.initials: MA
authors.lastname: Harris
authors.forename: Yasmin
authors.initials: Y
authors.lastname: Alam-Faruque
authors.forename: Judith A
authors.initials: JA
authors.lastname: Blake
authors.forename: Seth
authors.initials: S
authors.lastname: Carbon
authors.forename: Heiko
authors.initials: H
authors.lastname: Dietze
authors.forename: Emily C
authors.initials: EC
authors.lastname: Dimmer
authors.forename: Rebecca E
authors.initials: RE
authors.lastname: Foulger
authors.forename: David P
authors.initials: DP
authors.lastname: Hill
authors.forename: Varsha K
authors.initials: VK
authors.lastname: Khodiyar
authors.forename: Antonia
authors.initials: A
authors.lastname: Lock
authors.forename: Jane
authors.initials: J
authors.lastname: Lomax
authors.forename: Ruth C
authors.initials: RC
authors.lastname: Lovering
authors.forename: Prudence
authors.initials: P
authors.lastname: Mutowo-Meullenet
authors.forename: Tony
authors.initials: T
authors.lastname: Sawford
authors.forename: Kimberly
authors.initials: K
authors.lastname: Van Auken
authors.forename: Valerie
authors.initials: V
authors.lastname: Wood
authors.affiliation: Lawrence Berkeley National Laboratory, Genomics Division, Berkeley, CA 94720, USA. cjmungall@lbl.gov.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Mungall
mesh_terms: D019295:Computational Biology / Q000379:methods; D063990:Gene Ontology; D006801:Humans; D058977:Molecular Sequence Annotation; D011506:Proteins / Q000235:genetics
chemical_list: D011506:Proteins