Combining a binary input encoding scheme with RBFNN for globulin protein inter-residue contact map prediction

Authors:
Guang-Zheng Zhang;D. S. Huang;Z. H. Quan
Affiliations:
Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Science, P.O. Box 1130, Hefei, Anhui 230031, China and Department of Automation, University of Science and Te ...;Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Science, P.O. Box 1130, Hefei, Anhui 230031, China;Department of Automation, University of Science and Technology of China, Hefei, Anhui 230031, China
Venue:
Pattern Recognition Letters
Year:
2005

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Abstract

In this paper, we focus on protein inter-residue contacts map prediction, one of the most important intermediate steps to the protein folding problem, based on radial basis function neural network (RBFNN), and propose a novel binary encoding scheme for the purpose of learning the inter-residue contact patterns. The experimental evidence on globulin protein indicates the utility of our proposed encoding strategy. Moreover, the simulation results demonstrate that the network get a better performance for these proteins, whose residue length falls into the area of (100,300), and our proposed encoding strategy has promising future in the research on contacts map prediction problem.