Hongquan Su

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SAGE is a powerful tool to analysis whole-genome expression profiles. For improving the accuracy and efficiency of pattern recognition and clustering analysis, SAGE data is needed to be reducing dimensions due to its large quantities and high dimensions. A Poisson-Model based kernel (PMK) was proposed based on the Poisson distribution of the SAGE data.(More)
Due to the higher dimensional and nonlinear properties of the gene sequences, traditional self-organizing feature maps can't identify splice sites effectively. To circumvent the parameters study of the self-organizing feature maps, a method is presented based on the Kalman filter and the unscented transform which can identify splice sites effectively. By(More)
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