Olivier Rivoire

This paper introduces a new regularization strategy for generative protein models that improves the inference of multiscale sequence statistics, enabling the generation of functional and diverse protein sequences.

This paper develops a multi-stage approach combining phage display experiments, machine learning, and biophysical modeling to design antibodies with customized specificity profiles.

This paper presents a model showing how conformational changes in enzymes break a trade-off between specificity for transition states and product release, using substrate handles and chemical similarities between reaction states.

The paper investigates adaptive dependencies between enzymes in bacterial folate metabolism, showing that DHFR and TYMS form a modular unit that can adapt independently from the rest of the genome.

This paper introduces statistical coupling analysis (SCA) to decompose proteins into functional sectors and presents new methods for sector analysis in a Python software package.

The paper identifies conserved co-expression units in bacterial genomes beyond operons, showing that gene regulation can occur through segment-level feedback mechanisms.