Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (7): 171-174.DOI: 10.3778/j.issn.1002-8331.2010.07.052

• 图形、图像、模式识别 • Previous Articles     Next Articles

Multiple sequence analysis of hidden Markov model

LUO Ze-ju1,2,SONG Li-hong3   

  1. 1.Research Center of the Economy of the Upper Reaches of Yangtze River,Chongqing Technology and Business University,Chongqing 400067,China
    2.School of Computer Science & Information Engineering,Chongqing Technology and Business University,Chongqing 400067,China
    3.Economics and Management Center,Chongqing Technology and Business University,Chongqing 400067,China
  • Received:2008-09-17 Revised:2008-12-15 Online:2010-03-01 Published:2010-03-01
  • Contact: LUO Ze-ju

隐马尔可夫模型的多序列比对研究

罗泽举1,2,宋丽红3   

  1. 1.重庆工商大学 长江上游经济研究中心,重庆 400067
    2.重庆工商大学 计算机科学与信息工程学院,重庆 400067
    3.重庆工商大学 经济管理实验教学中心,重庆 400067
  • 通讯作者: 罗泽举

Abstract: A new multiple sequence alignment about Hidden Markov Models(HMMs) is researched,using the conservative feature of L value and consensus sequence,by increasing frequency factor,traditional HMMs learning algorithm is improved.Experiment indicates that not only the stability of the model is improved,but also a average improvement of 3.3% is achieved for protein family recognition by comparing the new algorithm with the traditional one.

Key words: hidden markov models, multiple sequence analysis, protein recognition

摘要: 研究一种关于隐马尔可夫模型的多序列比对,利用值和特征序列的保守性,通过增加频率因子,改进传统隐马尔可夫模型算法的不足。实验表明,新算法不但提高了模型的稳定性,而且应用于蛋白质家族识别,平均识别率比传统隐马尔可夫算法提高了3.3个百分点。

关键词: 隐马尔可夫模型, 多序列分析, 蛋白质识别

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