Managing the data deluge: data-driven GO category assignment improves while complexity of functional annotation increases.

ABSTRACT: The available curated data lag behind current biological knowledge contained in the literature. Text mining can assist biologists and curators to locate and access this knowledge, for instance by characterizing the functional profile of publications. Gene Ontology (GO) category assignment in free text already supports various applications, such as powering ontology-based search engines, finding curation-relevant articles (triage) or helping the curator to identify and encode functions. Popular text mining tools for GO classification are based on so called thesaurus-based--or dictionary-based--approaches, which exploit similarities between the input text and GO terms themselves. But their effectiveness remains limited owing to the complex nature of GO terms, which rarely occur in text. In c

SUBMITTER: Gobeill J 

PROVIDER: S-EPMC3706742 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature