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A Fuzzy Viterbi Algorithm for Improved Sequence Alignment and Searching of Proteins

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Applications of Evolutionary Computing (EvoWorkshops 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3449))

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Abstract

Profile HMMs based on classical hidden Markov models have been widely studied for identification of members belonging to protein sequence families. Classical Viterbi search algorithm which has been used traditionally to calculate log-odd scores of the alignment of a new sequence to a profile model is based on the probability theory. To overcome the limitations of the classical HMM and for achieving an improved alignment and better log-odd scores for the sequences belonging to a given family, we propose a fuzzy Viterbi search algorithm which is based on Choquet integrals and Sugeno fuzzy measures. The proposed search algorithm incorporates ascending values of the scores of the neighboring states while calculating the scores for a given state, hence providing better alignment and improved log-odd scores. The proposed fuzzy Viterbi algorithm for profiles along with classical Viterbi search algorithm has been tested on globin and kinase families. The results obtained in terms of log-odd scores, Z-scores and other statistical analysis establish the superiority of fuzzy Viterbi search algorithm.

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Author information

Authors and Affiliations

  1. Gippsland School of Computing and Information Technology, Monash University, Gippsland campus, Vic, 3842, Australia

    N. P. Bidargaddi, M Chetty & J Kamruzzaman

Authors
  1. N. P. Bidargaddi
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  2. M Chetty
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  3. J Kamruzzaman
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Editor information

Editors and Affiliations

  1. Johannes Gutenberg University, Mainz, Germany

    Franz Rothlauf

  2. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  3. Dipartimento di Ingegneria dell’Informazione, Università di Parma,  

    Stefano Cagnoni

  4. School of Mathematical and Computer Science, Heriot-Watt University, EH14 8AS, Edinburgh, UK

    David Wolfe Corne

  5. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  6. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

  7. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II of the University of Coimbra, 3030, Coimbra, Portugal

    Penousal Machado

  8. ICIS, Radboud University Nijmegen, The Netherlands

    Elena Marchiori

  9. Universidade de A Coruña, CP 15071, A Coruña, Spain

    Juan Romero

  10. School of Computing Sciences, University of East Anglia, UEA Norwich, NR4 7TJ, Norwich, UK

    George D. Smith

  11. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

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© 2005 Springer-Verlag Berlin Heidelberg

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Bidargaddi, N.P., Chetty, M., Kamruzzaman, J. (2005). A Fuzzy Viterbi Algorithm for Improved Sequence Alignment and Searching of Proteins. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_2

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  • DOI: https://doi.org/10.1007/978-3-540-32003-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25396-9

  • Online ISBN: 978-3-540-32003-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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