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A realistic assessment of methods for extracting gene/protein interactions from free text

Kabiljo, R. and Clegg, A.B. and Shepherd, Adrian J. (2009) A realistic assessment of methods for extracting gene/protein interactions from free text. BMC Bioinformatics 10 , p. 233. ISSN 1471-2105.

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Official URL: http://dx.doi.org/10.1186/1471-2105-10-233

Abstract

Background: The automated extraction of gene and/or protein interactions from the literature is one of the most important targets of biomedical text mining research. In this paper we present a realistic evaluation of gene/protein interaction mining relevant to potential non-specialist users. Hence we have specifically avoided methods that are complex to install or require reimplementation, and we coupled our chosen extraction methods with a state-of-the-art biomedical named entity tagger. Results: Our results show: that performance across different evaluation corpora is extremely variable; that the use of tagged (as opposed to gold standard) gene and protein names has a significant impact on performance, with a drop in F-score of over 20 percentage points being commonplace; and that a simple keyword-based benchmark algorithm when coupled with a named entity tagger outperforms two of the tools most widely used to extract gene/protein interactions. Conclusion: In terms of availability, ease of use and performance, the potential non-specialist user community interested in automatically extracting gene and/or protein interactions from free text is poorly served by current tools and systems. The public release of extraction tools that are easy to install and use, and that achieve state-of-art levels of performance should be treated as a high priority by the biomedical text mining community.

Item Type: Article
School or Research Centre: Birkbeck Schools and Research Centres > School of Science > Biological Sciences
Depositing User: Administrator
Date Deposited: 04 Aug 2010 14:09
Last Modified: 17 Apr 2013 12:33
URI: http://eprints.bbk.ac.uk/id/eprint/1091

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