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International Conference on Parallel Problem Solving from Nature

PPSN 1998: Parallel Problem Solving from Nature — PPSN V pp 959–967Cite as

Implementing genetic algorithms with sterical constraints for protein structure prediction

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1498))

Abstract

In this paper we present new kinds of genetic operators for protein structure prediction. These operators solve the problem of atom collisions during the conformational search. They restrict the search space to collision-free conformations by enforcing sterical constraints on the protein at each optimization step.

The results are compared to a standard genetic algorithm. The sterical constraint operators improve the results of the genetic algorithm by many orders of magnitude.

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Authors and Affiliations

  1. Lehrstuhl für Informatik V, Universität Mannheim, 68131, Mannheim, Germany

    Eckart Bindewald, Jürgen Hesser & Reinhard Männer

Authors
  1. Eckart Bindewald
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  2. Jürgen Hesser
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  3. Reinhard Männer
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Editor information

Agoston E. Eiben Thomas Bäck Marc Schoenauer Hans-Paul Schwefel

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© 1998 Springer-Verlag Berlin Heidelberg

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Bindewald, E., Hesser, J., Männer, R. (1998). Implementing genetic algorithms with sterical constraints for protein structure prediction. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN V. PPSN 1998. Lecture Notes in Computer Science, vol 1498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056937

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  • DOI: https://doi.org/10.1007/BFb0056937

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65078-2

  • Online ISBN: 978-3-540-49672-4

  • eBook Packages: Springer Book Archive

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