Jesse D Bloom

Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models

The paper improves the detection of positive selection in genes by using experimentally informed site-specific models, showing better identification of adaptive substitutions in four genes compared to traditional methods.

Accurate measurement of the effects of all amino-acid mutations to influenza hemagglutinin

The paper improves the accuracy of measuring amino-acid mutation effects on influenza hemagglutinin by using a helper virus, revealing mutation tolerance in antigenic sites and limited evolution capacity in stalk epitopes.

Software for the analysis and visualization of deep mutational scanning data

The paper introduces dms_tools, a software package for analyzing deep mutational scanning data to infer mutation impacts and visualize results with sequence-logo-style plots.

The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin

The paper uses deep mutational scanning to show that hemagglutinin has high mutational tolerance at antigenic sites, contributing to influenza's antigenic evolvability.

An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs

The paper develops an experimentally informed evolutionary model for beta-lactamase phylogenies, showing improved fit compared to existing models even for divergent homologs.

An experimentally determined evolutionary model dramatically improves phylogenetic fit

This paper develops an experimental evolutionary model for influenza nucleoprotein that improves phylogenetic fit compared to parameter-heavy models.