Using an Efficient Artificial Bee Colony Algorithm for Protein Structure Prediction on Lattice Models

Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/7253

Title:	Using an Efficient Artificial Bee Colony Algorithm for Protein Structure Prediction on Lattice Models
Authors:	林正堅
Contributors:	資訊工程系
Date:	2012-03
Issue Date:	2018-05-24 09:50:59 (UTC+8)
Abstract:	The well-known artificial bee colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms. The ABC system combines both local and global search methods in an attempt to balance exploration and exploitation processes, and hopefully, it can be successfully applied to solve real-world problems. In the past, the Science Magazine named the protein folding problem (PFP) as one of the 125 biggest unsolved problems in science. The PFP addresses the question of how the amino acid sequence (AAS) of a specific protein dictates its structure. In the study, we present a modified ABC (MABC) algorithm for the PFP with both 2D and 3D HP models. We demonstrate that our algorithm can be applied successfully to the protein folding problem based on the hydrophobic-polar lattice model. The simulation results show that the modified artificial bee colony algorithm can successfully be applied to the protein folding problem. © 2012 ISSN 1349-4198. (41 refs)
Relation:	International Journal of Innovative Computing, Information and Control
Appears in Collections:	[Department of Computer Science and Information Engineering] 【資訊工程系所】期刊論文

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