DocumentCode :
578348
Title :
Hybrid Artificial Bee Colony and Particle Swarm Optimization Approach to Protein Secondary Structure Prediction
Author :
Li, Mengwei ; Duan, Haibin ; Shi, Dalong
Author_Institution :
Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
fYear :
2012
fDate :
6-8 July 2012
Firstpage :
5040
Lastpage :
5044
Abstract :
Proteins are crucial in the biological processes, and their structure determines whether they can function well or not. Since the theory presented by Anfinsen that proteins´ space structure is entirely determined by the primary structure came out, it is possible for us to predict the structure of proteins through their primary structure without any experiment. In order to reach this target, the prediction problem can be formulated as an optimization problem that is set to find the lowest free energy conformation. In this paper, a hybrid Artificial Bee Colony (ABC) with Particle Swarm Optimization (PSO) Algorithm is used to solve this problem. Considering that the two algorithms have complementary characteristics, we combine them together and find out a better optimization results through this new approach. Experimental results have demonstrated the feasibility and effectiveness of our proposed approaches.
Keywords :
ant colony optimisation; bioinformatics; biological techniques; molecular biophysics; molecular configurations; particle swarm optimisation; proteins; artificial bee colony optimization; hybrid ABC-PSO algorithm; lowest free energy conformation; optimization problem; particle swarm optimization; protein secondary structure prediction; protein space structure; Amino acids; Computational modeling; Educational institutions; Optimization; Particle swarm optimization; Proteins; Solid modeling; Artificial Bee Colony; Particle Swarm Optimization; Protein structure prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
Type :
conf
DOI :
10.1109/WCICA.2012.6359433
Filename :
6359433
Link To Document :
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