Protein & Peptide Letters

Prof. Ben M. Dunn  
Department of Biochemistry and Molecular Biology
University of Florida
College of Medicine
P.O. Box 100245
Gainesville, FL


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

Author(s): 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

Order Reprints Order Eprints Rights & PermissionsPrintExport

Article Details

Page: [571 - 576]
Pages: 6
DOI: 10.2174/0929866043406283
Price: $58