title: Inter-residue spatial distance map prediction by using integrating GA with RBFNN.
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.
authors.affiliation: Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui 230031, China. gzzhang@iim.ac.cn
authors.forename: Guang-Zheng
authors.initials: GZ
authors.lastname: Zhang
authors.forename: De-Shuang
authors.initials: DS
authors.lastname: Huang
mesh_terms: 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
chemical_list: D011506:Proteins; D030262:Soybean Proteins