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Neural Networks

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Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 609))

Abstract

Neural networks are a class of intelligent learning machines establishing the relationships between descriptors of real-world objects. As optimisation tools they are also a class of computational algorithms implemented using statistical/numerical techniques for parameter estimate, model selection, and generalisation enhancement. In bioinformatics applications, neural networks have played an important role for classification, function approximation, knowledge discovery, and data visualisation. This chapter will focus on supervised neural networks and discuss their applications to bioinformatics.

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Author information

Authors and Affiliations

  1. School of Biosciences, University of Exeter, Exeter, UK

    Zheng Rong Yang

Authors
  1. Zheng Rong Yang
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Editor information

Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Dr. Bohr-Gasse 9, Wien, 1030, Austria

    Oliviero Carugo

  2. Research (A*STAR), Agency for Science & Technology, Biopolis Street 30, Singapore, 138671, Singapore

    Frank Eisenhaber

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© 2010 Humana Press, a part of Springer Science+Business Media, LLC

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Yang, Z.R. (2010). Neural Networks. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 609. Humana Press. https://doi.org/10.1007/978-1-60327-241-4_12

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  • DOI: https://doi.org/10.1007/978-1-60327-241-4_12

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-240-7

  • Online ISBN: 978-1-60327-241-4

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