ArticleDatabase : the journal of biological databases and curation2012
Text mining in the biocuration workflow: applications for literature curation at WormBase, dictyBase and TAIR.
Article in Database : the journal of biological databases and curation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 38 citations in OpenAlex.
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- Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature.BMC bioinformatics · 2018Article
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- SciLite: a platform for displaying text-mined annotations as a means to link research articles with biological data.Wellcome open research · 2016Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 1 institution in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.