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Neural Networks in Bioinformatics

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Handbook on Neural Information Processing

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 49))

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Abstract

Bioinformatics or computational biology is a multidisciplinary research area that combines molecular biology, computer science, and mathematics. Its aims are to organize, utilize and explore the vast amount of information obtained from biological experiments for understanding the relationships and useful patterns in data. Bioinformatics problems, such as protein structure prediction and sequence alignments, are commonly categorized as non-deterministic polynomial problems, and require sophisticated algorithms and powerful computational resources. Artificial Intelligence (AI) techniques have a proven track record in the development of many research areas in the applied sciences. Among the AI techniques, artificial neural networks (ANNs) and their variations have proven to be one of the more powerful tools in terms of their generalization and pattern recognition capabilities. In this chapter, we review a number of bioinformatics problems solved by different artificial neural network architectures.

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Authors and Affiliations

  1. The School of Computer Science at the University of Guelph, Guelph, Ontario, Canada

    Masood Zamani & Stefan C. Kremer

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  1. Masood Zamani
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  2. Stefan C. Kremer
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Correspondence to Masood Zamani .

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Editors and Affiliations

  1. , Dipto. Ingegneria dell'Informazione, Università degli Studi di Siena, Via Roma 56, Siena, 53100, Italy

    Monica Bianchini

  2. Fac. Ingegneria, Dipto. Ingegneria dell'Informazione, Università Siena, Via Roma 56, Siena, 53100, Italy

    Marco Maggini

  3. University of Canberra, School of Electrical and Information, Adjunct Professor, Mawson Lakes Campus, ACT, 2601, Australia

    Lakhmi C. Jain

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Zamani, M., Kremer, S.C. (2013). Neural Networks in Bioinformatics. In: Bianchini, M., Maggini, M., Jain, L. (eds) Handbook on Neural Information Processing. Intelligent Systems Reference Library, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36657-4_15

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  • DOI: https://doi.org/10.1007/978-3-642-36657-4_15

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