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Genetic algorithms with local search optimization for protein structure prediction problem

Authors:

Igor Berenboym,

Mireille AvigalAuthors Info & Claims

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

Pages 1097 - 1098

https://doi.org/10.1145/1389095.1389296

Published: 12 July 2008 Publication History

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Abstract

This paper presents a new Genetic Algorithm for Protein Structure Prediction problem in both 2D and 3D hydrophobic-hydrophilic lattice models, introduced in [1]. Our algorithm evolves a new local-search genetic operation (called Pull-Move and well described in [2]), into the standard GA¹ ([3,4]). The experiments show that performing a set of Pull-Moves in addition to standard genetic operations in GA (such as crossover and mutation) leads to significant energy improvements. The paper also introduces the Global Energy as fitness function and explains the advantages of utilizing it rather than the standard Free Energy. The experimental results are even more impressive when using the Global Energy as fitness function in GA.

References

[1]

K. F. Lau and K. A. Dill. Theory for Protein Mutability and Biogenesis. Proc. Nat. Acad. Sci., U.S.A. (1990), vol. 87, pp.638--642.

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[2]

N. Lesh, M. Mitzenmacher and S. Whitesize. A Complete and Effective Move Set for Simplified Protein Folding. Proceedings of the Seventh Annual International Conference on Research in Computational Molecular Biology (2003), pp.188--195.

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[3]

R. Unger and J. Moult. Genetic Algorithm for 3D Protein Folding Simulations. Proceedings of the 5th International Conference on Genetic Algorithms (1993), pp. 581--588.

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[4]

R. Unger and J. Moult. Genetic Algorithm for Protein Folding Simulations. Journal of Molecular Biology (1993) 231, pp.75--81.

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Cited By

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Misir M(2021)Generalized Automated Energy Function Selection for Protein Structure Prediction on 2D and 3D HP Models2021 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI50451.2021.9659895(1-6)Online publication date: 5-Dec-2021
https://doi.org/10.1109/SSCI50451.2021.9659895
Garza-Fabre MRodriguez-Tello EToscano-Pulido G(2013)Comparative Analysis of Different Evaluation Functions for Protein Structure Prediction Under the HP ModelJournal of Computer Science and Technology10.1007/s11390-013-1384-728:5(868-889)Online publication date: 17-Sep-2013
https://doi.org/10.1007/s11390-013-1384-7
Chira CHatami N(2012)Hybrid evolutionary algorithm with a composite fitness function for protein structure predictionProceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning10.1007/978-3-642-32639-4_23(184-191)Online publication date: 29-Aug-2012
https://dl.acm.org/doi/10.1007/978-3-642-32639-4_23
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Index Terms

Genetic algorithms with local search optimization for protein structure prediction problem
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
      1. Computational control theory
2. Theory of computation
  1. Design and analysis of algorithms
    1. Algorithm design techniques
      1. Backtracking
      2. Dynamic programming

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Published In

GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation

July 2008

1814 pages

ISBN:9781605581309

DOI:10.1145/1389095

Conference Chair:
Conor Ryan
University of Limerick, Ireland
,
Editor:
Maarten Keijzer
Chordiant Software International B.V., The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 12 July 2008

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GECCO08: Genetic and Evolutionary Computation Conference

July 12 - 16, 2008

GA, Atlanta, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Misir M(2021)Generalized Automated Energy Function Selection for Protein Structure Prediction on 2D and 3D HP Models2021 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI50451.2021.9659895(1-6)Online publication date: 5-Dec-2021
https://doi.org/10.1109/SSCI50451.2021.9659895
Garza-Fabre MRodriguez-Tello EToscano-Pulido G(2013)Comparative Analysis of Different Evaluation Functions for Protein Structure Prediction Under the HP ModelJournal of Computer Science and Technology10.1007/s11390-013-1384-728:5(868-889)Online publication date: 17-Sep-2013
https://doi.org/10.1007/s11390-013-1384-7
Chira CHatami N(2012)Hybrid evolutionary algorithm with a composite fitness function for protein structure predictionProceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning10.1007/978-3-642-32639-4_23(184-191)Online publication date: 29-Aug-2012
https://dl.acm.org/doi/10.1007/978-3-642-32639-4_23
Chira CHorvath DDumitrescu D(2011)Hill-Climbing search and diversification within an evolutionary approach to protein structure predictionBioData Mining10.1186/1756-0381-4-234:1Online publication date: 30-Jul-2011
https://doi.org/10.1186/1756-0381-4-23
Garza-Fabre MRodriguez-Tello EToscano-Pulido G(2011)Comparing alternative energy functions for the HP model of protein structure prediction2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949902(2307-2314)Online publication date: Jun-2011
https://doi.org/10.1109/CEC.2011.5949902
Chira C(2011)A hybrid evolutionary approach to protein structure prediction with lattice models2011 IEEE Congress of Evolutionary Computation (CEC)10.1109/CEC.2011.5949901(2300-2306)Online publication date: Jun-2011
https://doi.org/10.1109/CEC.2011.5949901
Băutu ALuchian H(2010)Protein structure prediction in lattice models with particle swarm optimizationProceedings of the 7th international conference on Swarm intelligence10.5555/1884958.1885011(512-519)Online publication date: 8-Sep-2010
https://dl.acm.org/doi/10.5555/1884958.1885011
Băutu ALuchian H(2010)Protein Structure Prediction in Lattice Models with Particle Swarm OptimizationSwarm Intelligence10.1007/978-3-642-15461-4_51(512-519)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15461-4_51
Chira CHorvath DDumitrescu D(2010)An evolutionary model based on hill-climbing search operators for protein structure predictionProceedings of the 8th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics10.1007/978-3-642-12211-8_4(38-49)Online publication date: 7-Apr-2010
https://dl.acm.org/doi/10.1007/978-3-642-12211-8_4

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Hybridization of genetic algorithm and local search in multiobjective function optimization: recommendation of GA then LS

Using messy genetic algorithms for solving the winner determination problem

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