Shoichi Yip

I am a PhD candidate in Physics supervised by Clément Nizak and Olivier Rivoire on the topic of High-throughput experiments and statistical data modeling for the engineering of enzyme specificity. I work at the crossroads of biophysics, biochemistry, bioinformatics, molecular biology and machine learning.

Research

Currently, I am working on a project that aims at modeling genotype-phenotype relations in biomolecules. In particular, my goal is to explain how biophysical properties emerge as a result of complex interactions between components of these systems (e.g. long-range interactions between amino acidic residues in proteins).

The model system of c hoice is a family of proteolytic enzymes called serine protease [1], which has been studied for a long time by biochemists but its internal mechanisms have not yet been well understood. The biophysical property of interest is their specificity profile, which is heterogeneous and cannot be exhaustively explained just in terms of geometrical / chemical properties (i.e. short-range interactions) [2].

I use a set up that a llows for high-throughput [3] and low-throughput measurements, that combines tools from bioinformatics, droplet microfluidics and molecular biology. These data can in turn be used to train machine-learning models that can capture coevolutionary signals and are also able to generate artificial proteins with the desired biophysical properties [4, 5].

Teaching

Links