Biologically, the function of a protein is highly related to its subcellular localization. Accordingly, it is necessary to develop an automatic yet 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. In this paper, the proposed Bayesian inference method and The Information Gain used to observed important information, Moreover, the Nearest Neighbor Classification is considerably effective for subcellular localization prediction in a supervised fashion
