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Bioinformatics. 2015 Jun 1;31(11):1872-4. doi: 10.1093/bioinformatics/btv045. Epub 2015 Jan 24.

ENVIRONMENTS and EOL: identification of Environment Ontology terms in text and the annotation of the Encyclopedia of Life.

Author information

1
Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.
2
Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Max Planck Institute for Marine Microbiology, Bremen, Germany, Jacobs University gGmbH, School of Engineering and Sciences, Bremen, Germany, Marine Biological Laboratory, Woods Hole, MA 02543, USA and National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA.

Abstract

The association of organisms to their environments is a key issue in exploring biodiversity patterns. This knowledge has traditionally been scattered, but textual descriptions of taxa and their habitats are now being consolidated in centralized resources. However, structured annotations are needed to facilitate large-scale analyses. Therefore, we developed ENVIRONMENTS, a fast dictionary-based tagger capable of identifying Environment Ontology (ENVO) terms in text. We evaluate the accuracy of the tagger on a new manually curated corpus of 600 Encyclopedia of Life (EOL) species pages. We use the tagger to associate taxa with environments by tagging EOL text content monthly, and integrate the results into the EOL to disseminate them to a broad audience of users.

AVAILABILITY AND IMPLEMENTATION:

The software and the corpus are available under the open-source BSD and the CC-BY-NC-SA 3.0 licenses, respectively, at http://environments.hcmr.gr.

PMID:
25619994
PMCID:
PMC4443677
DOI:
10.1093/bioinformatics/btv045
[Indexed for MEDLINE]
Free PMC Article

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