DocumentCode :
2370114
Title :
Prediction of protein long-range contacts using GaMC approach with sequence profile centers
Author :
Chen, Peng ; Li, Jinyan
Author_Institution :
Bioinf. Res. Center, Nanyang Technol. Univ., Singapore, Singapore
fYear :
2009
fDate :
1-4 Nov. 2009
Firstpage :
128
Lastpage :
135
Abstract :
In this paper, we apply an evolutionary optimization classifier, referred to as genetic algorithm-based multiple classifier (GaMC), to the long-range contacts prediction. As a result, about 44.1% contacts between long-range residues (with a sequence separation of at least 24 amino acids) are founded around the sequence profile (SP) centre when evaluating the top L/5 (L is the sequence length of protein) classified contacts if the SP centers are known. Meanwhile, with the knowledge of sequence profile center and the GaMC method, about 20.42% long-range contacts are correctly predicted. Results showed that SP center may be a sound pathway to predict contact map in protein structures. Availability- http://mail.ustc.edu.cn/~bigeagle/gamc.htm.
Keywords :
biology computing; genetic algorithms; pattern classification; proteins; evolutionary optimization classifier; genetic algorithm-based multiple classifier; protein long-range contacts; protein structures; sequence profile centers; Accuracy; Amino acids; Availability; Bioinformatics; Crystallography; Genetic engineering; Genetic programming; Neural networks; Protein engineering; Support vector machines; Long-range contact; evolutionary optimization; sequence profile; sequence profile centre;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-5121-0
Type :
conf
DOI :
10.1109/BIBMW.2009.5332116
Filename :
5332116
Link To Document :
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