DocumentCode
508060
Title
StSUT2 Structure Prediction Based on Nucleic Acid Sequence Using GA-BP
Author
Zhu, Zhengwei ; Guo, Yuying
Author_Institution
Sch. of Inf. Eng., Southwest Univ. of Sci. & Technol., Mianyang, China
Volume
3
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
149
Lastpage
153
Abstract
The protein secondary structure (PSS) prediction system presented in this paper is a subsystem of potato bioinformation research platform. The proposed method is a novel and practical PSS prediction method, which is based on nucleic acid sequence (NAS), uses an combined neural network (CNN) and takes an improved genetic algorithm (GA) to optimize the connection weights of CNN. The experimental results indicate that, not only the proposed method is feasible, but compared with the traditional PSS prediction methods, its prediction accuracy is higher, its use is more convenient, its search speed is faster and it has confidentiality in a certain degree.
Keywords
bioinformatics; genetic algorithms; macromolecules; neural nets; proteins; StSUT2 structure prediction; combined neural network; genetic algorithm; nucleic acid sequence; potato bioinformation research; protein secondary structure; Accuracy; Amino acids; Cellular neural networks; Genetic mutations; Neural networks; Neurons; Optimization methods; Prediction methods; Predictive models; Proteins; Potato; combined neural network; improved genetic algorithm; nucleic acid sequence; protein structure prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3736-8
Type
conf
DOI
10.1109/ICNC.2009.172
Filename
5365202
Link To Document