André J. Faure

This paper presents a method to identify allosteric sites in enzymes and applies it to Src kinase, producing the first comprehensive map of its allosteric control.

The paper uses deep learning to predict splicing regulatory effects and identify effective antisense oligonucleotides by analyzing systematic deletion scans of human exons.

The paper evaluates the stability and function of randomized hydrophobic protein cores across evolutionary distances, finding that allostery disrupts function despite stable cores.

This study quantifies how domain extensions in a PDZ protein reshape its energy and allosteric landscapes through extensive mutational analysis.

The paper uses genetic perturbation and machine learning to analyze the energetics of amyloid beta nucleation, revealing its genetic architecture and transition state structure.

The paper quantifies how mutations in JUN affect its binding to 54 human basic leucine zipper transcription factors, revealing that specificity is encoded by both positive and negative determinants.

This paper extends the Walsh-Hadamard transform to model epistasis in genetic landscapes with multiple alleles per position, enabling analysis of pairwise and higher-order interactions in simulated and empirical data.

The paper quantifies the effects of mutations on amyloid beta fibril nucleation using deep mutational scanning and identifies key residues that prevent nucleation, validating a cell-based assay for familial Alzheimer's disease mutations.

The paper uses deep mutational scanning to analyze the fitness landscape of an RNA structure, showing how mutational effects depend on multiple conformational states.

DiMSum is a pipeline for analyzing deep mutational scanning data that provides variant fitness estimates and error modeling to identify experimental issues.

This study systematically mutates the prion-like domain of TDP-43 to determine how sequence changes affect cellular toxicity and aggregation, finding that increased aggregation reduces toxicity.