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Standardized description of scientific evidence using the Evidence Ontology (ECO)
- Source :
- Database: The Journal of Biological Databases and Curation
- Publication Year :
- 2014
-
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.
- Subjects :
- Internet
Information retrieval
Computer science
Biological Ontologies
Web Ontology Language
Molecular Sequence Annotation
Genomics
Ontology (information science)
General Biochemistry, Genetics and Molecular Biology
Open Biomedical Ontologies
World Wide Web
Annotation
Mice
Saccharomyces
Vocabulary, Controlled
Controlled vocabulary
Databases, Genetic
Animals
Original Article
UniProt
General Agricultural and Biological Sciences
computer
Information Systems
computer.programming_language
Subjects
Details
- ISSN :
- 17580463
- Volume :
- 2014
- Database :
- OpenAIRE
- Journal :
- Database : the journal of biological databases and curation
- Accession number :
- edsair.doi.dedup.....95ae68e666226f0edff43910deb5512e