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Genetic Algorithms and Protein Folding

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Protein Structure Prediction

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 143))

Abstract

Genetic algorithms are, like neural networks, an example par excellence of an information-processing paradigm that was originally developed and exhibited by nature and later discovered by humans, who subsequently transformed the general principle into computational algorithms to be put to work in computers. Nature uses the principle of genetic heritage and evolution in an impressive way. Application of the simple concept of performance based reproduction of individuals (“survival of the fittest”) led to the rise of well-adapted organisms that can endure in a potentially adverse environment. Mutually beneficial interdependencies, cooperation, and even apparently altruistic behavior can emerge solely by evolution. The investigation of those phenomena is part of research in artificial life but is not dealt with here.

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Author information

Authors and Affiliations

  1. Max-Planck Institute for Molecular Genetics, Berlin, Germany

    Steffen Schulze-Kremer

Authors
  1. Steffen Schulze-Kremer
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Editor information

Editors and Affiliations

  1. Southern Cross Molecular, Freshford, Bath, UK

    David M. Webster

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© 2000 Humana Press Inc.

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Schulze-Kremer, S. (2000). Genetic Algorithms and Protein Folding. In: Webster, D.M. (eds) Protein Structure Prediction. Methods in Molecular Biology™, vol 143. Humana Press. https://doi.org/10.1385/1-59259-368-2:175

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  • DOI: https://doi.org/10.1385/1-59259-368-2:175

  • Publisher Name: Humana Press

  • Print ISBN: 978-0-89603-637-6

  • Online ISBN: 978-1-59259-368-2

  • eBook Packages: Springer Protocols

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