Vaibhav Mohanty

The paper introduces a method to directly estimate genotype fitness from time series data without assumptions on epistasis or iterative optimization, demonstrating its effectiveness across simulations and experimental datasets.

This paper designs biophysical fitness landscapes to control viral evolution, demonstrating suppression of SARS-CoV-2 escape variants through optimized antibody ensembles.

This paper develops a new mathematical framework, ProP Gen, to model evolutionary dynamics under phenotypic uncertainty and shows it explains phenomena like phenotypic buoying and improves predictions of bacterial persistence.

The paper derives an analytical theory for fitness landscape design (FLD) and validates it with experimental data on antibody binding affinities to influenza proteins.

This paper investigates thermally activated irreversible homogenization of G-quadruplexes in C9ORF72 hexanucleotide repeats, linking conformational changes to disease mechanisms.