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European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

EvoBIO 2013: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics pp 188–199Cite as

Impact of Different Recombination Methods in a Mutation-Specific MOEA for a Biochemical Application

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7833))

Abstract

Peptides play a key role in the development of drug candidates and diagnostic interventions, respectively. 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 peptides sequences which optimize several molecular properties. A mutation-specific fast non-dominated sorting GA (termed MSNSGA-II) was especially designed for this purpose.

In this work, an empirical study is presented about the performance of MSNSGA-II which is extended by optionally three different recombination operators. The main idea is to gain an insight into the significance of recombination for the performance of MSNSGA-II in general - and to improve the performance with these intuitive recombination methods for biochemical optimization. The benchmark test for this study is a three-dimensional optimization problem, using fitness functions provided by the BioJava library.

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Authors and Affiliations

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

    Susanne Rosenthal, Nail El-Sourani & Markus Borschbach

Authors
  1. Susanne Rosenthal
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  2. Nail El-Sourani
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  3. Markus Borschbach
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Editor information

Editors and Affiliations

  1. ISEGI, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal

    Leonardo Vanneschi

  2. Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University, 519 Light Hall, 37232, Nashville, USA

    William S. Bush

  3. Department of Veterinary Sciences, University of Torino, via Leonardi da Vinci 44, 10095, Grugliasco, TO, Italy

    Mario Giacobini

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Rosenthal, S., El-Sourani, N., Borschbach, M. (2013). Impact of Different Recombination Methods in a Mutation-Specific MOEA for a Biochemical Application. In: Vanneschi, L., Bush, W.S., Giacobini, M. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2013. Lecture Notes in Computer Science, vol 7833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37189-9_17

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  • DOI: https://doi.org/10.1007/978-3-642-37189-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37188-2

  • Online ISBN: 978-3-642-37189-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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