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Bioinformatics Advance Access published online on May 12, 2005
Bioinformatics, 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@oupjournals.org
Received February 21, 2005
Revised May 6, 2005
Accepted May 6, 2005

Article

Discovering patterns to extract protein-protein interactions from the literature: part II

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

1 State Key Laboratory of Intelligent Technology and Systems (LITS), Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China
2 School of Computer Science, University of Waterloo, N2L 3G1, Canada; State Key Laboratory of Intelligent Technology and Systems (LITS), Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

* To whom correspondence should be addressed.
Xiaoyan Zhu, E-mail: zxy-dcs{at}tsinghua.edu.cn


  Abstract

Motivation: An enormous number of protein-protein interaction relationships are buried in millions of research articles over the years, and accumulating. Rediscovering them automatically is a challenging bioinformatics task. Solutions to this problem are also far reaching, 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 [Huang et al, 2004], we have described how to generate English expression patterns related to protein-protein interactions, and it alone already has achieved precision and recall rates significantly higher than other automatic systems. This paper continues to present our theory, focusing on how to improve the patterns. An MDL-based pattern optimization algorithm is designed to reduce and merge patterns. This has significantly increased generalization power, hence the recall and precision rates, as confirmed by our experiments.

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


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