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A Hybrid Immune-Based System for the Protein Folding Problem

  • Carolina P. de Almeida
  • Richard A. Gonçalves
  • Myriam R. Delgado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4446)

Abstract

This paper describes hybrid algorithms based on artificial immune systems, fuzzy inference systems and tabu search to solve the Protein Folding Problem (PFP) in the 3D Hydrophobic-Polar model, which is a particular instance of the Combinatorial String Folding Problem in a cubic lattice. The proposed methodology aims at enhancing the Clonalg algorithm with a Fuzzy Aging Operator and Weak and Intensive Affinity Maturation. The aging operator uses a fuzzy system to decide which antibodies will be eliminated from the population before the selection stage. The Intensive Maturation employs a Tabu Search strategy. Penalty methods versus feasible search methods are also compared. The proposed hybrid algorithms are tested on a set of standard benchmark instances of PFP and the results attest the efficiency of the methodology.

Keywords

Local Search Tabu Search Fuzzy Inference System Maturation Stage Immune Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Carolina P. de Almeida
    • 1
  • Richard A. Gonçalves
    • 1
    • 2
  • Myriam R. Delgado
    • 1
  1. 1.Federal Technological University of Paraná, Curitiba, PRBrazil
  2. 2.Department of Computer Science, UNICENTRO, Guarapuava, PRBrazil

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