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Computational Systems Bioinformatics - Proceedings of the Conference CSB 2006
Many biological databases contain a large number of variables, among which events of interest may be very infrequent. Using a single data mining method to analyze such databases may not find adequate predictors. The HIV Drug Resistance Database at Stanford University stores sequential HIV-1 genotype-test results on patients taking antiretroviral drugs. We have analyzed the infrequent event of gene mutation changes by combining three data mining methods. We first use association rule analysis todoi:10.1142/18609475730049 fatcat:34opnnpvgng7fmc7imbic75vyi