Genetic Algorithm Feature-Based Resampling for Protein Structure Prediction

File Size Format
67446_1.pdf 814Kb Adobe PDF View
Title Genetic Algorithm Feature-Based Resampling for Protein Structure Prediction
Author Higgs, Trent Benjamin; Stantic, Bela; Hoque, Md Tamjidul; Sattar, Abdul
Publication Title 2010 IEEE World Congress on Computational Intelligence (WCCI 2010) Proceedings
Editor Hisao Ishibuchi
Year Published 2010
Place of publication Piscataway, NJ, USA
Publisher IEEE
Abstract Proteins carry out the majority of functionality on a cellular level. Computational protein structure prediction (PSP) methods have been introduced to speed up the PSP process due to manual methods, like nuclear magnetic resonance (NMR) and x-ray crystallography (XC) taking numerous months even years to produce a predicted structure for a target protein. A lot of work in this area is focused on the type of search strategy to employ. Two popular methods in the literature are: Monte Carlo based algorithms and Genetic Algorithms. Genetic Algorithms (GA) have proven to be quite useful in the PSP field, as they allow for a generic search approach, which alleviates the need to redefine the search strategies for separate sequences. They also lend themselves well to feature-based resampling techniques. Feature-based resampling works by taking previously computed local minima and combining features from them to create new structures that are more uniformly low in free energy. In this work we present a feature-based resampling genetic algorithm to refine structures that are outputted by PSP software. Our results indicate that our approach performs well, and produced an average 9.5% root mean square deviation (RMSD) improvement and a 17.36% template modeling score (TM-Score) improvement.
Peer Reviewed Yes
Published Yes
Alternative URI
Copyright Statement Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 978-1-4244-6909-3
Conference name 2010 IEEE World Congress on Computational Intelligence (WCCI)
Location Barcelona, Spain
Date From 2010-07-18
Date To 2010-07-23
Date Accessioned 2011-01-31
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Computation Theory and Mathematics; Data Format
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

Show simple item record

Griffith University copyright notice