Multiple sequence analysis of hidden Markov model

doi:10.3778/j.issn.1002-8331.2010.07.052

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-ju^1，2，SONG Li-hong³

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.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

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

CLC Number:

TP391

TN957.52

LUO Ze-ju^1，2，SONG Li-hong³. Multiple sequence analysis of hidden Markov model[J]. Computer Engineering and Applications, 2010, 46(7): 171-174.

罗泽举^1，2，宋丽红³. 隐马尔可夫模型的多序列比对研究[J]. 计算机工程与应用, 2010, 46(7): 171-174.

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Multiple sequence analysis of hidden Markov model

隐马尔可夫模型的多序列比对研究

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