Cancer Genomics
The central goal of cancer biology is to understand how the acquired genetic changes become responsible for deregulated cell growth and differentiation at molecular level. Cancer is not one disease but a family of diseases that makes early detection extremely difficult. Rapid development in high-throughput molecular techniques has resulted in the accumulation of vast amounts of cancer transcriptome data. These data have been generated with the intention of painting a molecular picture of each cancer subtype. Computational and mathematical tools are needed to decipher the complex interactions from these data. Expression signatures of disparate cancer types contain information on signaling pathways that may have been deregulated. The genes involved in deregulated pathways may be aberrantly and alternatively spliced; it is thus important to delineate deregulated pathways and the isoforms for genes that were part of those pathways.
My research is focused on developing computational and statistical methods to derive deregulated pathways and driver mutations from cancer genomic data. I also focus specifically on developing methods to understand the role of isoforms in pathway deregulation.
The Cancer Genome Atlas Research Network Symposium Meeting Lectures
