Inter-residue spatial distance map prediction by using integrating GA with RBFNN.
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.
Zhang
Guang-Zheng
GZ
Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui 230031, China. gzzhang@iim.ac.cn
Huang
De-Shuang
DS
D000465:Algorithms; D000595:Amino Acid Sequence; D019295:Computational Biology; D016571:Neural Networks, Computer; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D030262:Soybean Proteins / Q000737:chemistry
D011506:Proteins; D030262:Soybean Proteins