Vaishnavey SR

The paper develops a computational framework to analyze cyclic peptides, integrating data, improving sequence alignment, simulating thermal stability, and predicting melting points and metal binding.

The paper develops a scoring system to identify effective anti-methanogenic compounds by analyzing their structural and metabolic properties.

This paper introduces EscaPRRS, a Bayesian variational autoencoder that predicts antibody escape propensities of PRRSV GP5 mutants using structural and sequence data, showing strong correlation with binding affinities.

The paper develops a method to classify hydrolase functions using structural similarity of reaction cores, identifying enzyme backbones that can support multiple catalytic activities.