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A Hidden Markov Model and Immune Particle Swarm Optimization-Based Algorithm for Multiple Sequence Alignment

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

Multiple sequence alignment (MSA) is a fundamental and challenging problem in the analysis of biologic sequences. In this paper, an immune particle swarm optimization (IPSO) is proposed, which is based on the models of the vaccination and the receptor editing in immune systems. The proposed algorithm is used to train hidden Markov models (HMMs), further, an integration algorithm based on the HMM and IPSO for the MSA is constructed. The approach is tested on a set of standard instances taken from the Benchmark Alignment database, BAliBASE. Numerical simulated results are compared with those obtained by using the Baum-Welch training algorithm. The results show that the proposed algorithm not only improves the alignment abilities, but also reduces the time cost.

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Author information

Authors and Affiliations

  1. College of Computer Science, Jilin University, Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education, Changchun, 130012, China

    Hong-Wei Ge & Yan-Chun Liang

Authors
  1. Hong-Wei Ge
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  2. Yan-Chun Liang
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Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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Ge, HW., Liang, YC. (2005). A Hidden Markov Model and Immune Particle Swarm Optimization-Based Algorithm for Multiple Sequence Alignment. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_78

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  • DOI: https://doi.org/10.1007/11589990_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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