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Hybrid artificial bee colony and particle swarm optimization approach to protein secondary structure prediction

  • Mengwei Li*
  • , Haibin Duan
  • , Dalong Shi
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationWCICA 2012 - Proceedings of the 10th World Congress on Intelligent Control and Automation
Pages5040-5044
Number of pages5
DOIs
StatePublished - 2012
Event10th World Congress on Intelligent Control and Automation, WCICA 2012 - Beijing, China
Duration: 6 Jul 20128 Jul 2012

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference10th World Congress on Intelligent Control and Automation, WCICA 2012
Country/TerritoryChina
CityBeijing
Period6/07/128/07/12

Keywords

  • Artificial Bee Colony
  • Particle Swarm Optimization
  • Protein structure prediction

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