The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations.

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

Abstract

The Evidence and Conclusion Ontology (ECO) is a community resource for describing the various types of evidence that are generated during the course of a scientific study and which are typically used to support assertions made by researchers. ECO describes multiple evidence types, including evidence resulting from experimental (i.e., wet lab) techniques, evidence arising from computational methods, statements made by authors (whether or not supported by evidence), and inferences drawn by researchers curating the literature. In addition to summarizing the evidence that supports a particular assertion, ECO also offers a means to document whether a computer or a human performed the process of making the annotation. Incorporating ECO into an annotation system makes it possible to leverage the structure of the ontology such that associated data can be grouped hierarchically, users can select data associated with particular evidence types, and quality control pipelines can be optimized. Today, over 30 resources, including the Gene Ontology, use the Evidence and Conclusion Ontology to represent both evidence and how annotations are made.

Authors

  • Marcus C Chibucos
    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.
  • Deborah A Siegele
    Department of Biology, Texas A&M University, College Station, TX, 77843, USA.
  • James C Hu
    Department of Biochemistry and Biophysics, Texas A&M University and Texas AgriLife Research, College Station, TX, 77843, USA.
  • Michelle Giglio
    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.

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