Biology is at an exciting transition epoc that in many aspect is analogous to what happened in physics in the 16-17 century. Based on Brahe’s decades of observation, Kepler had the ingenious insight to identify the laws of planetary motion, which later lead to formation of  Newton’s theory of universal gravitation. Nowadays with technical advances biological data are collected at a rate far beyond  Brahe would  have imaged, and machine learning algorithms including artificial intellegence greatly facilitate pattern finding from large data sets compared to the challenges Kepler had faced. Now we are searching for general and specific principles as Newton did at his time. So it has never been a better time for physicists to study biological problems. 

Speficically, my lab asks the question how a cell maintains and controls its phenotype. Cells from multicellular organisms can have identical genomes but different phenotypes with different physiology and functions. During development, embryonic stem cells differentiate into different phenotypes and differentiated cells can also reprogram into another phenotype. In the languarage of physics a cell is a nonlinear dynamical systems, and a stable phenotype corresponds to a stable attractor or limit cycle of the dynamical system. Cell phenotypic transitions (CPTs) are examples of rate processes. Rate theories have been central topic in physics and chemistry for more than century, and recently cell phenoptypic transitions emerge as a new frontier of rate theory studies about transition dynamics in nonequilibrium systems. My lab studies CPTs through quantitative single cell measurements,  and computational/theoretical analyses.