The genomic era of cancer research is developing rapidly, enabled by various high-throughput platforms, especially the emergence of NGS sequencing technologies. Computational analysis to profile cancer genome aberrations has revealed a staggering number of diverse abnormalities, including DNA copy number alterations, epigenetic aberrations and somatic mutations.
Integrative analysis of these data sets to discover underlying mechanisms and understand biological processes remains a challenge. This talk will discuss our computational work in dissecting this complexity and propose a framework to harness the full potential of large-scale integrated cancer genomic data.
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