Research Goals

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 initiation, progression and therapeutic resistance

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

Featured Publications


Center for Personal Dynamics Regulomes

CTD2 Data Portal: Provides raw and analyzed primary data of chemical and genetic screens.

CTD2 Dashboard: Provides access to validated data and the ability to view results assembled across multiple CTD2 Centers’ findings. It allows easy exploration by computational experts and those with little bioinformatics experience.

GitHub repository

Human Tumor Atlas Network

The Cancer Target Discovery and Development (CTD2) initiative is a community resource project, making strides in turning genomic research into effective cancer treatments.