Radial basis function neural network optimized by a genetic algorithm for soybean protein sequence residue spatial distance prediction

The spatial ordering information of amino acid residues in a protein primary sequence is an important factor in the determination of protein three-dimensional structure (tertiary structure). In this paper, we describe a radial basis function neural network, whose hidden centers and radial basis function widths are optimized by a genetic algorithm, 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.