We are interested in elucidating tumor evolutionary dynamics, novel therapeutic targets, and the genotype to phenotype map in cancer. A unifying theme of our research is to exploit ‘omic’ data derived from clinically annotated samples in robust computational frameworks coupled with iterative experimental validation in order to advance our understanding of cancer systems biology. In particular, we employ advanced genomic techniques, computational and mathematical modeling, and powerful model systems in order to:
1.) Model the evolutionary dynamics of tumor progression and therapeutic resistance and metastasis
2) Elucidate disease etiology and novel molecular targets through integrative analyses of high-throughput omic data
3) Develop techniques for the systems-level interpretation of genotype-phenotype associations in cancer