Feature Selection for Large Scale Cancer Associated Gene Expression Profiling Data
Hung-Ming's main research is focused on developing a framework for high-throughput gene signatures for a certain disease phenotype prediction using feature selection techniques. The framework is aimed at providing biologically meaningful gene sets having good classification performance and stable selection, and will be expected to signature identification derived from multi �omics heterogeneous profiles. His research interests include Microarray/Next Generation Sequencing Data Analysis, High Throughput Gene/Probe Selection and Preprocessing, Genome Wide miRNA-mRNA Interactions, and Cancer Genomics.
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