Support Vector Machines for predicting protein structural class |
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| Authors: | Yu-Dong Cai Xiao-Jun Liu Xue-biao Xu Guo-Ping Zhou |
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| Institution: | (1) Shanghai Research Centre of Biotechnology, Chinese Academy of Sciences, Shanghai, 200233, China;(2) Institute of Cell, Animal and Population Biology University of Edinburgh, West Mains Road, Edinburgh, EH9 3JT, U.K;(3) Department of Computing Science, University of Wales, College of Cardiff, Queens Buildings, Newport Road, PO Box 916, Cardiff, CF2 3XF, U.K;(4) Department of Structural Biology, Burnham Institute, La Jolla, California, 92037, USA |
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| Abstract: | Background We apply a new machine learning method, the so-called Support Vector Machine method, to predict the protein structural class. Support Vector Machine method is performed based on the database derived from SCOP, in which protein domains are classified based on known structures and the evolutionary relationships and the principles that govern their 3-D structure. |
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