title: A guide to best practices for Gene Ontology (GO) manual annotation.
abstract: The Gene Ontology Consortium (GOC) is a community-based bioinformatics project that classifies gene product function through the use of structured controlled vocabularies. A fundamental application of the Gene Ontology (GO) is in the creation of gene product annotations, evidence-based associations between GO definitions and experimental or sequence-based analysis. Currently, the GOC disseminates 126 million annotations covering >374,000 species including all the kingdoms of life. This number includes two classes of GO annotations: those created manually by experienced biocurators reviewing the literature or by examination of biological data (1.1 million annotations covering 2226 species) and those generated computationally via automated methods. As manual annotations are often used to propagate functional predictions between related proteins within and between genomes, it is critical to provide accurate consistent manual annotations. Toward this goal, we present here the conventions defined by the GOC for the creation of manual annotation. This guide represents the best practices for manual annotation as established by the GOC project over the past 12 years. We hope this guide will encourage research communities to annotate gene products of their interest to enhance the corpus of GO annotations available to all. DATABASE URL: http://www.geneontology.org.
authors.affiliation: Saccharomyces Genome Database, Department of Genetics, Stanford University, 300 Pasteur Drive, MC-5477 Stanford, CA 94305, USA.
authors.forename: Rama
authors.initials: R
authors.lastname: Balakrishnan
authors.forename: Midori A
authors.initials: MA
authors.lastname: Harris
authors.forename: Rachael
authors.initials: R
authors.lastname: Huntley
authors.forename: Kimberly
authors.initials: K
authors.lastname: Van Auken
authors.forename: J Michael
authors.initials: JM
authors.lastname: Cherry
mesh_terms: D001686:Biological Phenomena / Q000235:genetics; D057225:Data Mining; D003663:Decision Trees; D058977:Molecular Sequence Annotation / Q000379:methods*; D012015:Reference Standards; D012689:Sequence Homology, Nucleic Acid