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Genome Biol. 2008;9 Suppl 2:S7. doi: 10.1186/gb-2008-9-s2-s7. Epub 2008 Sep 1.

Text mining for biology--the way forward: opinions from leading scientists.

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  • 1Stanford University, Stanford, California, 94305-5444, USA.

Abstract

This article collects opinions from leading scientists about how text mining can provide better access to the biological literature, how the scientific community can help with this process, what the next steps are, and what role future BioCreative evaluations can play. The responses identify several broad themes, including the possibility of fusing literature and biological databases through text mining; the need for user interfaces tailored to different classes of users and supporting community-based annotation; the importance of scaling text mining technology and inserting it into larger workflows; and suggestions for additional challenge evaluations, new applications, and additional resources needed to make progress.

PMID:
18834498
[PubMed - indexed for MEDLINE]
PMCID:
PMC2559991
Free PMC Article
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