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  • 标题:Applying Hidden Markov Model to Protein Sequence Alignment
  • 本地全文:下载
  • 作者:Er. Neeshu Sharma ; Dinesh Kumar ; Reet Kamal Kaur
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2011
  • 卷号:2
  • 期号:3
  • 页码:1031-1035
  • 出版社:TechScience Publications
  • 摘要:Hidden markov models is a statistical tool largely used to study protein alignments and profile analysis of a set of proteins. Finite state machines like HMM move through a series of states and produce output either when the machine has reached a particular state or when it is moving from state to another. It generates a protein sequence by emitting amino acids as it progresses through a series of states. Multiple sequence alignment is a powerful technique that is used by modern bioinformatics systems almost in all their applications. The biomedical methods and algorithms used in MSA have vast importance in solving a series of related biological problems. The well-known and widely used statistical method of characterizing the spectral properties of the residues of a genomic or proteomic pattern is the HMM approach. Profile HMMs have proved to offer a robust solution for MSAX-?
  • 关键词:HiddenMarkovModel HMM; Multiple Sequence;Alignment PairwiseSequence Alignment; Alignment;Profile;HMM
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