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A Survey of Multiple Sequence Alignment Techniques

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Book cover Intelligent Computing Theories and Methodologies (ICIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9225))

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Abstract

Multiple sequence alignment (MSA) is a basic step in many bioinformatics analyses, and also a NP-hard problem. In order to improve the speed, accuracy and cater to the requirement of large-scale sequences alignment, a wide variety of MSA methods and softwares have been subsequently developed. In this article, we will systematically review the wildly used methods and introduce their practical results on the benchmark Balibase 3.0 references. We come to the conclusion that computational complexity still is the bottleneck of MSA. We also consider future development of MSA methods with respect to applying of more different technologies and the prospect of parallelization of MSA.

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Acknowledgement

This work was supported by Shenzhen Municipal Science and Technology Innovation Council (Grant No. CXZZ20140904154910774, Grant No.JCYJ20140417172417174, Grant No. JCYJ20140904154645958, Grant No. JCYJ20130329151843309) and China Postdoctoral Science Foundation funded project (Grant No. 2014M560264).

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Authors and Affiliations

  1. Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Heilongjiang, China

    Xiao-Dan Wang, Jin-Xing Liu, Yong Xu & Jian Zhang

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  1. Xiao-Dan Wang
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  2. Jin-Xing Liu
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  3. Yong Xu
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  4. Jian Zhang
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Correspondence to Xiao-Dan Wang .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytecnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

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Wang, XD., Liu, JX., Xu, Y., Zhang, J. (2015). A Survey of Multiple Sequence Alignment Techniques. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9225. Springer, Cham. https://doi.org/10.1007/978-3-319-22180-9_52

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  • DOI: https://doi.org/10.1007/978-3-319-22180-9_52

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-22180-9

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