Wong, Ka-ChunKa-ChunWongProf. LEUNG Kwong SakWong, Man-HonMan-HonWong2023-03-232023-03-232010Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, 2010, GECCO '10, pp. 15 - 22978-145030072-8http://hdl.handle.net/20.500.11861/7545This 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.enProtein Structure PredictionMultimodal OptimizationHP Lattice ModelRelative EncodingAbsolute EncodingDistance MetricCrowdingFitness SharingEvolutionary AlgorithmConference Paper10.1145/1830483.1830513