The biological landscape is made up of millions of variables that interact in complex and often seemingly random ways. I am applying principles from physical and computational sciences to the study of biology to find patterns in these interactions, to obtain insight into population genetics, human evolution, and diseases including cancer.
Gurinder S. “Mickey” Atwal and colleagues are applying insights from the physical and computational sciences to the study of population genetics and human disease. The Atwal lab has modeled the process by which genetic variants, or alleles, have evolved in the last 100,000 years of human history. This has recently led to surprising insights about the role of p53, a master tumor suppressor gene, in female fertility and furthered our understanding of how complex gene networks evolve. The lab has analyzed the comparative genomics and physical organization of cancerrelated genes and their role in mediating tumorigenesis across numerous tissue types. Recently, they have begun to focus efforts on understanding cancer genome evolution on shorter time scales by analyzing nucleotide sequences from single cells.
