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Text mining in the biocuration workflow: applications for literature curation at WormBase, dictyBase and TAIR.
Van Auken, Kimberly; Fey, Petra; Berardini, Tanya Z; Dodson, Robert; Cooper, Laurel; Li, Donghui; Chan, Juancarlos; Li, Yuling; Basu, Siddhartha; Muller, Hans-Michael; Chisholm, Rex; Huala, Eva; Sternberg, Paul W.
Affiliation
  • Van Auken K; Division of Biology, California Institute of Technology, 1200 E. California Boulevard, Pasadena, CA 91125, USA. vanauken@caltech.edu
Database (Oxford) ; 2012: bas040, 2012.
Article in En | MEDLINE | ID: mdl-23160413
ABSTRACT
WormBase, dictyBase and The Arabidopsis Information Resource (TAIR) are model organism databases containing information about Caenorhabditis elegans and other nematodes, the social amoeba Dictyostelium discoideum and related Dictyostelids and the flowering plant Arabidopsis thaliana, respectively. Each database curates multiple data types from the primary research literature. In this article, we describe the curation workflow at WormBase, with particular emphasis on our use of text-mining tools (BioCreative 2012, Workshop Track II). We then describe the application of a specific component of that workflow, Textpresso for Cellular Component Curation (CCC), to Gene Ontology (GO) curation at dictyBase and TAIR (BioCreative 2012, Workshop Track III). We find that, with organism-specific modifications, Textpresso can be used by dictyBase and TAIR to annotate gene productions to GO's Cellular Component (CC) ontology.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Periodicals as Topic / Caenorhabditis elegans / Arabidopsis / Databases, Genetic / Dictyostelium / Data Mining / Workflow Limits: Animals Language: En Journal: Database (Oxford) Year: 2012 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Periodicals as Topic / Caenorhabditis elegans / Arabidopsis / Databases, Genetic / Dictyostelium / Data Mining / Workflow Limits: Animals Language: En Journal: Database (Oxford) Year: 2012 Document type: Article Affiliation country: United States