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Multiobjectivizing the HP Model for Protein Structure Prediction

  • Mario Garza-Fabre
  • Eduardo Rodriguez-Tello
  • Gregorio Toscano-Pulido
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7245)

Abstract

The hydrophobic-polar (HP) model for protein structure prediction abstracts the fact that hydrophobic interactions are a dominant force in the protein folding process. This model represents a hard combinatorial optimization problem, which has been widely addressed using evolutionary algorithms and other metaheuristics. In this paper, the multiobjectivization of the HP model is proposed. This originally single-objective problem is restated as a multiobjective one by decomposing the conventional objective function into two independent objectives. By using different evolutionary algorithms and a large set of test cases, the new alternative formulation was compared against the conventional single-objective problem formulation. As a result, the proposed formulation increased the search performance of the implemented algorithms in most of the cases. Both two- and three-dimensional lattices are considered. To the best of authors’ knowledge, this is the first study where multiobjective optimization methods are used for solving the HP model.

Keywords

Multiobjectivization protein structure prediction HP model 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mario Garza-Fabre
    • 1
  • Eduardo Rodriguez-Tello
    • 1
  • Gregorio Toscano-Pulido
    • 1
  1. 1.Information Technology LaboratoryCINVESTAV-TamaulipasCd. VictoriaMéxico

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