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Protein & Peptide Letters
ISSN (Print): 0929-8665
ISSN (Online): 1875-5305
VOLUME: 11
ISSUE: 6
DOI: 10.2174/0929866043406283      Price:  $58









Inter-Residue Spatial Distance Map Prediction by Using Integrating Ga with Rbfnn

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Author(s): Guang-Zheng Zhang and De-Shuang Huang
Pages 571-576 (6)
Abstract:
The spatial ordering information of amino acid residue in protein primary sequence is an important determinant of protein three-dimensional structure. In this paper, we describe a radial basis function neural network (RBFNN), whose hidden centers and basis function widths are optimized by a genetic algorithm (GA), for the purpose of predicting three dimensional spatial distance location from primary sequence information. Experimental evidence on soybean protein sequences indicates the utility of this approach.
Keywords:
spatial distance, radial basis function neural network, genetic algorithm, soybean protein, prediction
Affiliation:
Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences Department of Automation, University of Science&Technology of China P.O. Box 1130, Hefei, Anhui 230031,C71hina.