Life is often presented as a pinnacle of complexity with the root of the difficulty laying in the multiplicity of its constituents and the intricacy of their interactions. Knowing every constituent and interaction is, however, unlikely to solve all problems.
More generally, an exhaustive characterization of living systems may neither be sufficient nor necessary for their understanding and engineering. Instead, a critical challenge for biology is to achieve a proper “coarse-grained”, low-dimensional description of living systems that captures the relative functional significance of their constituents and interactions.
We pursue two synergistic approaches in the group:
1. a statistical, data-driven, approach to biology, focusing on developing new quantitative frameworks and algorithms for the analysis of live-imaging and single-cell sequencing data
2. physical modeling of living systems to help parametrize and explore when a data-driven approach isn't warranted or possible