Interdisciplinary Bio Central
 
Etc. (Bioinformatics/Computational biology/Molecular modeling)

A Rule-Based Approach Toward Extraction of Interaction Information from Scientific Literature
Ming Cheng 1 and Doheon Lee1,*
1Department of Biosystems, Korea Advanced Institute of Science and Technology,Daejeon, Republic of Korea
*Corresponding author
  Published : October 31, 2006
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Synopsis

Scientific literature is the most reliable and comprehensive source of knowledge about molecular interaction networks. This knowledge is scattered in scientific literature written in natural languages, much time and labor have to be spent on manually extracting biological molecule interactions from literature. There have been many efforts for automatic extraction of biomedical knowledge from literatures. We propose a pattern matching algorithm with multiple Part-Of-Speech tagging based rules which could effectively reduce the required number of patterns and increase the recovery rate of traditional pattern matching algorithm. Various situations in biomedical texts are studied in the paper. The recovery and accuracy rate of the system is estimated to be 68.7% and 93.0%, respectively.

Keyword: Rule-Based Approach , Interaction Information, Scientific Literature
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