Jared Galloway

Across 119 monoclonal germinal centers, B cell affinity rises reliably despite divergent phylogenies. Selection is noisy but persistent; mutability limits exploration. A DMS-based landscape shows saturating fitness and survivorship biases.

The paper estimates neutral mutation rates and fitness effects of mutations in influenza proteins using phylogenetic analysis of over 100,000 sequences, revealing context-dependent patterns across viruses.

The paper uses simulation-based deep learning to infer the affinity-fitness response function in germinal centers from experimental data.

This study examines how SARS-CoV-2 evolved to escape 1,603 antibodies by analyzing mutation dynamics and selective pressures over 3.5 years of the pandemic.

The paper estimates mutation rates across SARS-CoV-2 genome sites and identifies factors influencing these rates, finding significant variability and patterns related to gene boundaries, sequence context, and RNA structure.

The paper uses deep mutational scanning to analyze CYP2C19 variants, revealing a tradeoff between substrate specificity and protein abundance.

The paper develops a method to identify mutations with shifted effects across DMS experiments on SARS-CoV-2 spike homologs, finding some mutations show >1,000-fold differences in impact across variants.

The paper introduces msprime 1.0, a high-performance simulation tool for ancestry and mutation in population genetics, showing it is faster and more memory efficient than existing alternatives.