Best Practices in Manual Annotation with the Gene Ontology.

Journal: Methods in molecular biology (Clifton, N.J.)
Published Date: Jan 1, 2017

Abstract

The Gene Ontology (GO) is a framework designed to represent biological knowledge about gene products' biological roles and the cellular location in which they act. Biocuration is a complex process: the body of scientific literature is large and selection of appropriate GO terms can be challenging. Both these issues are compounded by the fact that our understanding of biology is still incomplete; hence it is important to appreciate that GO is inherently an evolving model. In this chapter, we describe how biocurators create GO annotations from experimental findings from research articles. We describe the current best practices for high-quality literature curation and how GO curators succeed in modeling biology using a relatively simple framework. We also highlight a number of difficulties when translating experimental assays into GO annotations.

Authors

  • Sylvain Poux
    Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Department of Microbiology and Immunology and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore MD, USA, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, 1211 Geneva, Switzerland, Department of Medicine and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore MD, USA, Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA, School of Information, University of South Florida, Tampa, FL, 33647, USA, Genomics Division, Lawrence Berkeley National Lab, 1 Cyclotron Rd., Berkeley, 94720 CA USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland, ETH Zurich, Department of Computer Science, Universitätstr. 19, 8092 Zürich, Switzerland, SIB Swiss Institute of Bioinformatics, Universitätstr. 6, 8092 Zürich, Switzerland and University College London, Gower St, London WC1E 6BT, UK.
  • Pascale Gaudet
    Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Department of Microbiology and Immunology and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore MD, USA, SIB Swiss Institute of Bioinformatics, 1 Rue Michel Servet, 1211 Geneva, Switzerland, Department of Medicine and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore MD, USA, Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA, School of Information, University of South Florida, Tampa, FL, 33647, USA, Genomics Division, Lawrence Berkeley National Lab, 1 Cyclotron Rd., Berkeley, 94720 CA USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, Geneva, Switzerland, ETH Zurich, Department of Computer Science, Universitätstr. 19, 8092 Zürich, Switzerland, SIB Swiss Institute of Bioinformatics, Universitätstr. 6, 8092 Zürich, Switzerland and University College London, Gower St, London WC1E 6BT, UK.

Keywords

External Resources

Popular Topics
Recent Journals