Semi-automated curation of protein subcellular localization: a text mining-based approach to Gene Ontology (GO) Cellular Component curation.

ABSTRACT:

Background

Manual curation of experimental data from the biomedical literature is an expensive and time-consuming endeavor. Nevertheless, most biological knowledge bases still rely heavily on manual curation for data extraction and entry. Text mining software that can semi- or fully automate information retrieval from the literature would thus provide a significant boost to manual curation efforts.

Results

We employ the Textpresso category-based information retrieval and extraction system (http://www.textpresso.org), developed by WormBase to explore how Textpresso might improve the efficiency with which we manually curate C. elegans proteins to the Gene Ontology's Cellular Component Ontology. Using a training set of sentences that describe results of localization experiments

SUBMITTER: Van Auken K 

PROVIDER: S-EPMC2719631 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature