Standardized description of scientific evidence using the Evidence Ontology (ECO)

Marcus C Chibucos; Christopher J Mungall; Rama Balakrishnan; Karen R Christie; Rachael P Huntley; Owen White; Judith A Blake; Suzanna E Lewis; Michelle Giglio

doi:10.1093/database/bau075

Standardized description of scientific evidence using the Evidence Ontology (ECO)

Database (Oxford). 2014 Jul 22:2014:bau075. doi: 10.1093/database/bau075. Print 2014.

Authors

Marcus C Chibucos¹, Christopher J Mungall², Rama Balakrishnan², Karen R Christie², Rachael P Huntley², Owen White³, Judith A Blake², Suzanna E Lewis², Michelle Giglio³

Affiliations

¹ Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA, Saccharomyces Genome Database, Department of Genetics, Stanford University, Stanford, CA 94305, USA, Computational Biology and Bioinformatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK, Department of Epidemiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USAInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA, Saccharomyces Genome Database, Department of Genetics, Stanford University, Stanford, CA 94305, USA, Computational Biology and Bioinformatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK, Department of Epidemiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA [email protected].
² Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA, Saccharomyces Genome Database, Department of Genetics, Stanford University, Stanford, CA 94305, USA, Computational Biology and Bioinformatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK, Department of Epidemiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
³ Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA, Saccharomyces Genome Database, Department of Genetics, Stanford University, Stanford, CA 94305, USA, Computational Biology and Bioinformatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK, Department of Epidemiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USAInstitute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA, Saccharomyces Genome Database, Department of Genetics, Stanford University, Stanford, CA 94305, USA, Computational Biology and Bioinformatics, The Jackson Laboratory, Bar Harbor, ME 04609, USA, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK, Department of Epidemiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA and Department of Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.

Abstract

The Evidence Ontology (ECO) is a structured, controlled vocabulary for capturing evidence in biological research. ECO includes diverse terms for categorizing evidence that supports annotation assertions including experimental types, computational methods, author statements and curator inferences. Using ECO, annotation assertions can be distinguished according to the evidence they are based on such as those made by curators versus those automatically computed or those made via high-throughput data review versus single test experiments. Originally created for capturing evidence associated with Gene Ontology annotations, ECO is now used in other capacities by many additional annotation resources including UniProt, Mouse Genome Informatics, Saccharomyces Genome Database, PomBase, the Protein Information Resource and others. Information on the development and use of ECO can be found at http://evidenceontology.org. The ontology is freely available under Creative Commons license (CC BY-SA 3.0), and can be downloaded in both Open Biological Ontologies and Web Ontology Language formats at http://code.google.com/p/evidenceontology. Also at this site is a tracker for user submission of term requests and questions. ECO remains under active development in response to user-requested terms and in collaborations with other ontologies and database resources. Database URL: Evidence Ontology Web site: http://evidenceontology.org.

Publication types

Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Animals
Databases, Genetic*
Genomics / methods*
Internet*
Mice
Molecular Sequence Annotation / methods*
Saccharomyces
Vocabulary, Controlled*

Abstract

Publication types

MeSH terms

Grants and funding