Multi-level clustering support vector machine trees for improved protein local structure prediction
by Wei Zhong; Jieyue He; Xiujuan Chen; Yi Pan
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 9, No. 2, 2014

Abstract: Local protein structure prediction is one of important tasks for bioinformatics research. In order to further enhance the performance of local protein structure prediction, we propose the Multi-level Clustering Support Vector Machine Trees (MLSVMTs). Building on the multi-cluster tree structure, the MLSVMTs model uses multiple SVMs, each of which is customized to learn the unique sequence-to-structure relationship for one cluster. Both the combined 5 × 2 CV F test and the independent test show that the local structure prediction accuracy of MLSVMTs is significantly better than that of one-level K-means clustering, Multi-level clustering and Clustering Support Vector Machines.

Online publication date: Tue, 21-Oct-2014

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