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Diversification Strategies in Differential Evolution Algorithm to Solve the Protein Structure Prediction Problem

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

The protein structure prediction is considered as one of the most important open problems in biology and bioinformatics due the huge amount of plausible shapes that a protein can assume. The objective of this paper is to apply the Differential Evolution (DE) algorithm employing two simple diversification strategies known as generation gap and Gaussian perturbation to solve the protein structure prediction problem in the backbone and side-chain model. To test our approaches the 1PLW, 1ZDD and 1CRN proteins were used and the standard DE algorithm was compared with DE using the diversification approaches and with some state-of-art algorithms. Also, the genotypic diversity was analyzed during the algorithm run, showing the impacts generated by the diversification mechanisms. Despite its simplicity, the proposed approaches achieved competitive results.

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Authors and Affiliations

  1. Graduate Program in Applied Computing, Departament of Computer Science, State University of Santa Catarina, Joinville, Brazil

    Pedro Henrique Narloch & Rafael Stubs Parpinelli

Authors
  1. Pedro Henrique Narloch
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  2. Rafael Stubs Parpinelli
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Correspondence to Rafael Stubs Parpinelli .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Narloch, P.H., Parpinelli, R.S. (2017). Diversification Strategies in Differential Evolution Algorithm to Solve the Protein Structure Prediction Problem. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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