Supantha Dey

OpenKinetics Predictor unifies thirteen enzyme kinetic predictors behind one interface and API; on E. coli iML1515, eight kcat predictors correlate pairwise at r 0.08 to 0.67.

RealKcat predicts enzyme kinetics from sequence using a curated dataset and embeddings, showing sensitivity to catalytic mutations and robustness across evaluations.

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.

This paper uses molecular simulations and a graph neural network to identify potential methanogenesis inhibitors and their biochemical properties.

The paper analyzes gene expression profiles from RTS,S malaria vaccine doses to assess efficacy and identify cytokine responses associated with protection.