Inter-Residue Spatial Distance Map Prediction by Using Integrating Ga with Rbfnn
Guang-Zheng Zhang and De-Shuang Huang
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.
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
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