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A Benchmark on the Interaction of Basic Variation Operators in Multi-objective Peptide Design Evaluated by a Three Dimensional Diversity Metric and a Minimized Hypervolume

  • Conference paper
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 227))

Abstract

Peptides play a key role in the development of drug candidates and diagnostic interventions. The design of peptides is cost-intensive and difficult in general for several well-known reasons. Multi-objective evolutionary algorithms (MOEAs) introduce adequate in silico methods for finding optimal peptide sequences which optimize several molecular properties. A mutation-specific fast non-dominated sorting GA (termed MSNSGA-II) is especially designed for this purpose.

In addition, an advanced study is conducted in this paper on the performance of MSNSGA-II when driven by further mutation and recombination operators. These operators are application-specific developments or adaptions. The fundamental idea is to gain an insight in the interaction of these components with regard to an improvement of the convergence behavior and diversity within the solution set according to the main challenge of a low number of generations. The underlying application problem is a three-dimensional minimization problem and satisfies the requirements in biochemical optimization: the objective functions have to determine clues for molecular features which - as a whole- have to be as generic as possible. The fitness functions are provided by the BioJava library. Further, the molecular search space is examined by a landscape analysis. An overview of the fitness functions in the molecular landscapes is given and correlation analysis is performed.

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Authors and Affiliations

  1. FHDW, Faculty of Computer Science, Chair of Optimized Systems, University of Applied Sciences, Hauptstr. 2, D-51465, Bergisch Gladbach, Germany

    Susanne Rosenthal & Markus Borschbach

Authors
  1. Susanne Rosenthal
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  2. Markus Borschbach
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Corresponding author

Correspondence to Susanne Rosenthal .

Editor information

Editors and Affiliations

  1. , Leiden Institute of Advanced, Leiden University, Niels Bohrweg 1, Leiden, 2333CA, Netherlands

    Michael Emmerich

  2. , Leiden Institute of Advanced, Leiden University, Niels Bohrweg 1, Leiden, 2333CA, Netherlands

    Andre Deutz

  3. , Depto. de Computacion, CINVESTAV-IPN, Av. IPN No. 2508, Col. San Pedro Zacatenco, Mexico, 07360, Mexico

    Oliver Schuetze

  4. , Leiden Institute of Advanced, Leiden University, Niels Bohrweg 1, Leiden, 2333CA, Netherlands

    Thomas Bäck

  5. , Luxembourg Centre for, University of Luxembourg, Avenue des Hauts Fourneaux 7, Belval, 4362, Luxembourg

    Emilia Tantar

  6. , Computer Science and, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, 1359, Luxembourg

    Alexandru-Adrian Tantar

  7. , Bordeaux Mathematical Institute, Université Bordeaux I, cours de la Libération 351, Talence cedex, 33405, France

    Pierre Del Moral

  8. , UFR Sciences et Modélisation, Université Bordeaux Segalen, 3ter place de la Victoire, Bordeaux, 33076, France

    Pierrick Legrand

  9. Faculty of Sci., Tech. & Communication, Computer Science and, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, 1359, Luxembourg

    Pascal Bouvry

  10. , Depto. de Computatción, CINVESTAV-IPN, Av. IPN No. 2508, Col. San Pedro Zacatenco, Mexico, 07360, Mexico

    Carlos A. Coello

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Rosenthal, S., Borschbach, M. (2013). A Benchmark on the Interaction of Basic Variation Operators in Multi-objective Peptide Design Evaluated by a Three Dimensional Diversity Metric and a Minimized Hypervolume. In: Emmerich, M., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV. Advances in Intelligent Systems and Computing, vol 227. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01128-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-01128-8_10

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-01127-1

  • Online ISBN: 978-3-319-01128-8

  • eBook Packages: EngineeringEngineering (R0)

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