J4 ›› 2012, Vol. 50 ›› Issue (02): 320-322.

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An HMM Based Transcription Factor Name Mining Algorithm

WU Xiaozhou1, WAN Liming2, HAN Xiaosong1, LIANG Yanchun1, WU Chunguo1,3   

  1. 1. College of Computer Science and Technology, Key Laboratory for Symbol Computation and Knowledge Engineeringof National Education Ministry, Jilin University, Changchun 130012, China|2. Research Institute on General Development and Evaluation of Equipment, EAAF of PLA, Beijing 100076, China;3. School of Business, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2011-12-29 Online:2012-03-26 Published:2012-03-21
  • Contact: WU Chunguo E-mail:wucg@jlu.edu.cn

Abstract:

A text mining algorithm named HMMTFM (hidden Markov model based transcription factor name mining) was presented. The proposed algorithm does not need a dictionary of transcription factor names. A small verb set is defined to filter sentences. Transcription factor names are mined according to the part of speech tagged by hidden Markov model. Experimental results show that the recall rate and precision of HMMTFM come to 74.2% and 77.9%, respectively.

Key words: hidden Markov model, transcription factor, text mining, promoter, bioinformatics

CLC Number: 

  • TP18