Posts classified under: DBDS

Our research in the Translational Cancer Evolution Laboratory focuses on the stochastic biological processes underlying cancer evolution with the goal to improve the prognosis and treatment of tumors. We develop computational methods to learn from large-scale biological data sets and design mathematical models to predict patient outcomes, generate novel hypotheses, and explain observations on a mechanistic level. We apply these methods to genomic data from clinically-annotated patient cohorts to advance precision medicine. For example, we have designed methods to optimize cancer early detection strategies and to find optimal combination therapies to minimize the risk of cancer relapse.

My research is focused on understanding the health implications of the myriad decisions that are made by corporations and governments every day — decisions that profoundly shape the social and economic worlds in which we live and work. I analyze population based datasets to demonstrate the health implications of economic and social factors that can give the public and policy makers evidence to support new strategies for promoting health and well-being. In all of his work, I focus on the implications of these exposures for health inequalities. Since often policy and programmatic changes can take decades to influence health, my research also includes more basic research in understanding biological signals that may act as early warning signs of systemic disease, in particular accelerated aging. I examine how social and economic policy changes influence a range of early markers of disease and aging, with a particular recent focus on DNA methylation.

https://profiles.stanford.edu/david-rehkopf

Interests lie at the nexus of physics, biology, and biotechnology. His research is concerned with developing new approaches to biological measurement and applying these approaches to problems of both fundamental and medical interest. Areas of interest include genomic diagnostics, systems biology, microbial ecology, and single cell genomics. Read more about the Quake Lab.

https://profiles.stanford.edu/stephen-quake

Our group uses statistical and computational methods to study questions in genomics and evolutionary biology. Much of our work focuses on questions relating to genetic variation and evolution. An important part of our work is in developing appropriate statistical and computational approaches that can yield new insights into biological data.

https://profiles.stanford.edu/jonathan-pritchard