Protein Structure Prediction with Evolutionary Algorithms

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Description

Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

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10 p.

Creation Information

Hart, W.E.; Krasnogor, N.; Pelta, D.A. & Smith, J. February 8, 1999.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM, and Livermore, CA (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

Physical Description

10 p.

Notes

OSTI as DE00003477

Medium: P; Size: 10 pages

Source

  • Genetic and Evolutionary Computation Conference, Orlando, FL (US), 07/13/1999--07/17/1999

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  • Report No.: SAND99-0329C
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 3477
  • Archival Resource Key: ark:/67531/metadc675879

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Creation Date

  • February 8, 1999

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

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  • April 6, 2017, 6:53 p.m.

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Hart, W.E.; Krasnogor, N.; Pelta, D.A. & Smith, J. Protein Structure Prediction with Evolutionary Algorithms, article, February 8, 1999; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc675879/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.