Universal approximation using radial-basis-function networks
Neural Computation
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Machine Learning
A Theory of Networks for Approximation and Learning
A Theory of Networks for Approximation and Learning
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Protein-protein interactions play a very important role in many biological processes, for example, information transfer along signaling pathways, and enzyme catalysis. Recently, scientists tried to predict the protein-protein interaction interface from sequences. Since the number of protein 3D structure still increase slowly comparing to the number of protein sequences, it may be a good idea to predict the protein-protein interface from sequences directly. In this paper, the compositions and conserved functions of the amino acids in the protein interface are studied, and the information of secondary structures is added. In addition, we used radio basis function network to predict the protein interface with adding some useful biochemical features.