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We introduce a novel parallel combined classifiers method for the problems of protein classification and remote homology detection. The method use parallel computing idea to rebuild the high accuracy SVM-based algorithm and the complete coverage nearest neighbor algorithm. We run the two classifiers simultaneously and combine the output result together to reduce the running time and improve the classification...
Selecting differentially expressed genes (DEGs) is one of the most important tasks in microarray applications. However, the sample sizes typically used in current cancer studies may only partially reflect the widely altered gene expressions in cancers. By analyzing three large cancer datasets, we show that, in each cancer, a wide range of functional modules are altered and have high disease classification...
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