title: Orthogonal kernel machine for the prediction of functional sites in proteins.
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.
authors.affiliation: Department of Computer Science, Exeter University, Exeter EX4 4QF, UK. z.r.yang@ex.ac.uk
authors.forename: Zheng Rong
authors.initials: ZR
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D001665:Binding Sites; D003198:Computer Simulation; D008956:Models, Chemical; D008969:Molecular Sequence Data; D011485:Protein Binding; D011506:Proteins / Q000032:analysis / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins