Richard D. Berlin
Center for Cell Analysis & Modeling

CCAM Faculty

Ji Yu

Assistant Professor of Genetics and Develpmental Biologyy

Contact Information

Dr. Ji Yu
University of Connecticut Health Center
Center for Cell Analysis & Modeling
263 Farmington Avenue
Farmington, CT 06030-6406
Phone: 860-679-7680
Fax: 860- 679-1039
jyu@uchc.edu
Yu Lab Web Page

Research Interests

The complexity of biological phenomena is both architectural, that is, due to the large number of interacting molecular components underlining any biological processes, and also a result of the inherent heterogeneity in this network of molecules. To describe these systems in a quantitative way, we need new tools to analyze the behavior of single cells and single molecules, which our lab is striving to develop and to apply to many compelling biological questions.

Single molecule biophysics

A strong barrage of single molecule experimental work during the past decade has greatly expanded our capability in dissecting the real time dynamics of complicated molecular interactions. A particular problem we are interested in is the DNA segregation in prokaryotes during cell division. Traditionally believed to be totally passive the process has now been widely re-examined due to many new evidences pointing to an active partitioning process. We will develop single molecule assays for both in vitro and in live cells and try to understand the molecular mechanism of this segregation process.

Gene networks in single cells

It has been long observed that genetically identical cells develop very different phenotypes, but the reason for it is not well understood. We are particularly interested in the effects related to the small size of the cells – hence the significant stochastic fluctuation in gene networks, leading to variations in cellular behavior. Some initial steps have been taken to test this idea, but we are far from a quantitative understanding, especially in higher eukaryotic cells. Our lab will pursue the studying of cell-to-cell heterogeneity by combining techniques of single cell gene expression analysis with theoretical modeling. The important question is what are the controlling parameters in determining the distribution of gene expression in individual cells.