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Computational Intelligence in Bioinformatics

  • Conference paper
Transactions on Rough Sets III

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 3400))

Abstract

Computational intelligence poses several possibilities in Bioinformatics, particularly by generating low-cost, low-precision, good solutions. Rough sets promise to open up an important dimension in this direction. The present article surveys the role of artificial neural networks, fuzzy sets and genetic algorithms, with particular emphasis on rough sets, in Bioinformatics. Since the work entails processing huge amounts of incomplete or ambiguous biological data, the knowledge reduction capability of rough sets, learning ability of neural networks, uncertainty handling capacity of fuzzy sets and searching potential of genetic algorithms are synergistically utilized.

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Author information

Authors and Affiliations

  1. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, 700 108, India

    Sushmita Mitra

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  1. Sushmita Mitra
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2005 Springer-Verlag Berlin Heidelberg

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Mitra, S. (2005). Computational Intelligence in Bioinformatics. In: Peters, J.F., Skowron, A. (eds) Transactions on Rough Sets III. Lecture Notes in Computer Science, vol 3400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427834_6

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  • DOI: https://doi.org/10.1007/11427834_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25998-5

  • Online ISBN: 978-3-540-31850-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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