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A Randomized Algorithm for Distance Matrix Calculations in Multiple Sequence Alignment

  • Conference paper
Knowledge Exploration in Life Science Informatics (KELSI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3303))

Abstract

Multiple sequence alignment (MSA) is a vital problem in biology. Optimal alignment of multiple sequences becomes impractical even for a modest number of sequences [1] since the general version of the problem is NP-hard. Because of the high time complexity of traditional MSA algorithms, even today’s fast computers are not able to solve the problem for large number of sequences. In this paper we present a randomized algorithm to calculate distance matrices which is a major step in many multiple sequence alignment algorithms. The basic idea employed is sampling (along the lines of [2]).

This research has been supported in part by the NSF Grants CCR-9912395 and ITR-0326155.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, University of Connecticut, 371 Fairfield Road, Unit 2155, Storrs, Connecticut, 06269-2155

    Sanguthevar Rajasekaran, Vishal Thapar, Hardik Dave & Chun-Hsi Huang

Authors
  1. Sanguthevar Rajasekaran
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  2. Vishal Thapar
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  3. Hardik Dave
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  4. Chun-Hsi Huang
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Editor information

Editors and Affiliations

  1. Faculty of Sciences, School of Mathematics and Computing, University of Southern Queensland, 4350, Toowoomba, QLD, Australia

    Jesús A. López

  2. Istituto di Ricerche Farmacologiche “Mario Negri”, Via Eritrea 62, 20157, Milano, Italy

    Emilio Benfenati

  3. School of Biomedial Sciences, Bioinformatics Research Group, University of Ulster, Cromore Road, BT52 1SA, Coleraine, Northern Ireland, UK

    Werner Dubitzky

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© 2004 Springer-Verlag Berlin Heidelberg

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Rajasekaran, S., Thapar, V., Dave, H., Huang, CH. (2004). A Randomized Algorithm for Distance Matrix Calculations in Multiple Sequence Alignment. In: López, J.A., Benfenati, E., Dubitzky, W. (eds) Knowledge Exploration in Life Science Informatics. KELSI 2004. Lecture Notes in Computer Science(), vol 3303. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30478-4_4

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  • DOI: https://doi.org/10.1007/978-3-540-30478-4_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23927-7

  • Online ISBN: 978-3-540-30478-4

  • eBook Packages: Springer Book Archive

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