Survey on the Multiple Sequence Alignment Based on Hidden Markov Model

摘要：

In computational biology, Multiple sequence alignment(MSA) is one of the basic problems.Realistic problem instances of MSA are computadonally intractable for exact algorithms.One way to tackle MSA is to use Hidden Markov Models (HMMs),which are known to be very powerful in the related problem domain of speech recognition.The HMMs can be trained with different methods.And we can use a GA for optimizing the HM structure,as well as hybrid GA-HMM training.In this paper,we will introduce several different methods to train the HMMs,and will show the advantages and disadvantages of each method,making comprehensive analysis to them.Analysis of the behavior of the algorithm sheds light on possible improvement.

关键词： Hidden Markov Models GA-HMM training Hybrid Generic Algorithm

作者: Wenjuan Ji Jun Sun

作者单位: School of Information Technology,Jiangnan University,Wuxi,214122,China

会议类型: 国际会议

会议名称: 2008年国际电子商务、工程及科学领域的分布式计算和应用学术研讨会(2008 International Symposium on Distributed Computing and Applications for Business Engineering and Science)

会议地点: 大连

会议语种:英文

页码: 654-660

在线出版日期: 2008-07-27（万方平台首次上网日期，不代表论文的发表时间）