Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7545
Title: Protein structure prediction on a lattice model via multimodal optimization techniques
Authors: Wong, Ka-Chun 
Prof. LEUNG Kwong Sak 
Wong, Man-Hon 
Issue Date: 2010
Publisher: Association for Computing Machinery (ACM)
Source: Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, 2010, GECCO '10, pp. 15 - 22
Journal: Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 
Abstract: This paper considers the protein structure prediction problem as a multimodal optimization problem. In particular, de novo protein structure prediction problems on the 3D Hydrophobic-Polar (HP) lattice model are tackled by evolutionary algorithms using multimodal optimization techniques. In addition, a new mutation approach and performance metric are proposed for the problem. The experimental results indicate that the proposed algorithms are more effective than the state-of-the-arts algorithms, even though they are simple. Copyright 2010 ACM.
Type: Conference Proceedings
URI: http://hdl.handle.net/20.500.11861/7545
ISBN: 978-145030072-8
DOI: 10.1145/1830483.1830513
Appears in Collections:Applied Data Science - Publication

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