Title :
Orthogonal kernel Machine for the prediction of functional sites in proteins
Author :
Yang, Zheng Rong
Author_Institution :
Dept. of Comput. Sci., Exeter Univ., UK
Abstract :
A novel pattern recognition algorithm called an orthogonal kernel machine (OKM) is presented for the prediction of functional sites in proteins. Two novelties in OKM are that the kernel function is specially designed for measuring the similarity between a pair of protein sequences and the kernels are selected using the orthogonal method. Based on a set of well-recognized orthogonal kernels, this algorithm demonstrates its superior performance compared with other methods. An application of this algorithm to a real problem is presented.
Keywords :
biology; biotechnology; pattern recognition; proteins; support vector machines; bioinformatics; orthogonal kernel machine; pattern recognition; protein sequences; Amino acids; Biological information theory; Decision trees; Encoding; Human immunodeficiency virus; Kernel; Liver diseases; Neural networks; Pattern recognition; Protein sequence; Bioinformatics; kernel-based approach and orthogonal method; pattern recognition; Algorithms; Amino Acid Sequence; Artificial Intelligence; Binding Sites; Computer Simulation; Models, Chemical; Molecular Sequence Data; Protein Binding; Proteins; Sequence Alignment; Sequence Analysis, Protein; Structure-Activity Relationship;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2004.840723