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Bioinformatics Advance Access originally published online on May 12, 2005
Bioinformatics 2005 21(15):3294-3300; doi:10.1093/bioinformatics/bti493
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Discovering patterns to extract protein–protein interactions from the literature: Part II

Yu Hao 1, Xiaoyan Zhu 1,*, Minlie Huang 1 and Ming Li 1,2,3

1State Key Laboratory of Intelligent Technology and Systems (LITS), Department of Computer Science and Technology, Tsinghua University Beijing, 100084, China
2School of Computer Science, University of Waterloo N2L 3G1, Canada
3City University of Hong Kong Tat Chee Avenue, Kowloon, Hong Kong SAR

*To whom correspondence should be addressed.

Motivation: An enormous number of protein–protein interaction relationships are buried in millions of research articles published over the years, and the number is growing. Rediscovering them automatically is a challenging bioinformatics task. Solutions to this problem also reach far beyond bioinformatics.

Results: We study a new approach that involves automatically discovering English expression patterns, optimizing them and using them to extract protein–protein interactions. In a sister paper, we described how to generate English expression patterns related to protein–protein interactions, and this approach alone has already achieved precision and recall rates significantly higher than those of other automatic systems. This paper continues to present our theory, focusing on how to improve the patterns. A minimum description length (MDL)-based pattern-optimization algorithm is designed to reduce and merge patterns. This has significantly increased generalization power, and hence the recall and precision rates, as confirmed by ourexperiments.

Availability: http://spies.cs.tsinghua.edu.cn

Contact: zxy-dcs{at}tsinghua.edu.cn

Received on February 21, 2005; revised on May 6, 2005; accepted on May 6, 2005

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