Veda Sheersh Boorla

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.

BindPred predicts protein-protein binding affinity from amino acid sequences using language model embeddings and gradient boosting trees, achieving high correlation on a benchmark dataset.

MechFind predicts enzyme mechanisms from reaction stoichiometry, achieving 72% accuracy on a training set and generating 18,000 novel hypotheses across 28,412 reactions.

CatPred predicts in vitro enzyme kinetic parameters using deep learning, achieving competitive performance with uncertainty quantification on diverse datasets.