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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