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Hybrid method for predicting protein location in cells

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Hybrid method for predicting protein location in cells Predicting Protein Subcellular Location Using Hybrid Approach

Shih-Hao Chen Han Wen Hsiao Xiaowen Hong

Shih-Hao Chen Han-Wen Hsiao Wen-Hung Hsiao

Taichung Healthcare and Management University of biological information by

Institute of Bioinformatics, Taichung Healthcare and Management University

Biologically, the function of a protein is highly related to its subcellular localization.

It is necessary to develop a reliable method for protein subcellular localization prediction, especially when large-scale genome sequences are to be analyzed. Various methods have been proposed to perform the task . The results, however, are not satisfactory in terms of effectiveness and efficiency. A hybrid approach using naïve Bayesian classifier with information gain ratio and k-nearest neighbor classifier is presented. The total accuracy for a set of 17655 proteins can reach up to 91.5 %.

Key Words: subcellular localization, function prediction

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