Our group (created January 2008) develops computational imaging and modeling approaches to gain a quantitative understanding of key processes in cell biology. We work along three complementary lines, in close collaboration with several wet biology labs, computer scientists and physicists:

• Computational imaging: we develop algorithms to reliably and efficiently extract quantitative information from microscopy images. For example, one such algorithm automatically detects rod-shaped bacteria in fluorescence microscopy images (Zhang et al., ISBI 2006)  Other algorithms detect chromosome loci in thousands of individual yeast cells and compute high-resolution  probability maps showing the territorial organization of genes in the nucleus (Berger et al., Nat. Meth. 2008).
  

• Modeling: we develop computational models based on physical principles in order to understand the quantitative information extracted from imaging data; by confronting theoretical predictions to experiments, we hope to establish predictive models of cell biological functions. Our current focus is on the spatial organization and dynamics of the genome inside the nucleus and its role in gene expression and genomic stability.