Evaluating Computational Gene Ontology Annotations.

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

Abstract

Two avenues to understanding gene function are complementary and often overlapping: experimental work and computational prediction. While experimental annotation generally produces high-quality annotations, it is low throughput. Conversely, computational annotations have broad coverage, but the quality of annotations may be variable, and therefore evaluating the quality of computational annotations is a critical concern.In this chapter, we provide an overview of strategies to evaluate the quality of computational annotations. First, we discuss why evaluating quality in this setting is not trivial. We highlight the various issues that threaten to bias the evaluation of computational annotations, most of which stem from the incompleteness of biological databases. Second, we discuss solutions that address these issues, for example, targeted selection of new experimental annotations and leveraging the existing experimental annotations.

Authors

  • Nives Skunca
    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 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 Nat
  • Richard J Roberts
    New England Biolabs, 240 County Road, Ipswich, MA, 01938, USA.
  • Martin Steffen
    Department of Biomedical Engineering, Boston University, Boston, MA, USA.

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