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A novel ab-initio genetic-based approach for protein folding prediction

Published: 07 July 2007 Publication History

Abstract

In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary structure information is used in the initialization of the genetic algorithm; ii) An enhanced 3D spatial representation called cube-octahedron is used, also, an expansion technique is proposed in order to reduce the computational complexity and spatial constraints; iii) Data preprocessing of geometric features to characterize the cube-octahedron using twelve basic vectors to define the nodes. Additionally, biological information (torsion angles, bond angles and secondary structure conformations) was pre-processed through an analysis of all possible combinations of the basic vectors which satisfy the biological constrains defined by the spatial representation; and iv) Hashing techniques were used to improve the computational efficiency. The pre-processed information was stored in hash tables, which are intensively used by the genetic algorithm. Some experiments were carried out to validate the proposed model obtaining very promising results.

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  • (2018)An Efficient Ant Colony Optimization Algorithm for Protein Structure Prediction2018 12th International Symposium on Medical Information and Communication Technology (ISMICT)10.1109/ISMICT.2018.8573710(1-6)Online publication date: Mar-2018
  • (2016)Protein Folding Modeling with Neural Cellular Automata Using RosettaProceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2931720(1307-1312)Online publication date: 20-Jul-2016
  • (2016)Guided macro-mutation in a graded energy based genetic algorithm for protein structure predictionComputational Biology and Chemistry10.1016/j.compbiolchem.2016.01.00861:C(162-177)Online publication date: 1-Apr-2016
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  1. A novel ab-initio genetic-based approach for protein folding prediction

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        cover image ACM Conferences
        GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
        July 2007
        2313 pages
        ISBN:9781595936974
        DOI:10.1145/1276958
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        Published: 07 July 2007

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        Author Tags

        1. 3D- FCC spatial representation
        2. ab-initio methods
        3. genetic algorithms
        4. protein folding problem

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        GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
        Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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        View all
        • (2018)An Efficient Ant Colony Optimization Algorithm for Protein Structure Prediction2018 12th International Symposium on Medical Information and Communication Technology (ISMICT)10.1109/ISMICT.2018.8573710(1-6)Online publication date: Mar-2018
        • (2016)Protein Folding Modeling with Neural Cellular Automata Using RosettaProceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2931720(1307-1312)Online publication date: 20-Jul-2016
        • (2016)Guided macro-mutation in a graded energy based genetic algorithm for protein structure predictionComputational Biology and Chemistry10.1016/j.compbiolchem.2016.01.00861:C(162-177)Online publication date: 1-Apr-2016
        • (2013)Protein folding with cellular automata in the 3D HP modelProceedings of the 15th annual conference companion on Genetic and evolutionary computation10.1145/2464576.2466812(1595-1602)Online publication date: 6-Jul-2013
        • (2013)Neighborhood Selection in Constraint-Based Local Search for Protein Structure PredictionProceedings of the 26th Australasian Joint Conference on AI 2013: Advances in Artificial Intelligence - Volume 827210.1007/978-3-319-03680-9_5(44-55)Online publication date: 1-Dec-2013
        • (2009)Biologically-implemented genetic algorithm for protein engineeringProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1569934(233-240)Online publication date: 8-Jul-2009

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