Chris Jennings-Shaffer

The paper presents a deep learning approach that uses phylogenetic dynamic program outputs to predict edges in maximum parsimony trees, achieving high accuracy on simulated and empirical datasets.

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.

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.