Kai S Shimagaki

This study evaluates epistasis inference methods using temporal genetic data across different evolutionary regimes, finding that accuracy depends on selection, recombination, and genetic drift.

The paper shows that glycan N276 at Env affects resistance to VRC01-class bNAbs, with its impact varying based on Env, bNAb, and producer cell glycosylation.

The paper quantifies HIV-1 evolution in humans and macaques, showing similar fitness effects of mutations and a pattern of rapid fitness gains preceding bnAb development.

This paper develops a method to predict viral sensitivity to antibodies using genetic sequences and antibody similarities, showing it outperforms existing approaches and can predict neutralization values for unseen viruses.

This paper introduces a method to efficiently infer epistasis from temporal genetic data, finding strong negative epistasis between beneficial mutations in HIV-1 evolution.

popDMS infers mutation effects from DMS data by applying population genetics theory, showing consistency across replicates and outperforming existing methods.

The paper introduces a method to reduce parameters in protein family models by selecting sequence motifs, leading to Hopfield-Potts models that capture residue conservation and covariation with fewer patterns.