Rahul Kaushik

This study benchmarks protein language models for predicting protein crystallization propensity and identifies novel potentially crystallizable proteins.

This paper introduces APR-Score, a machine-learning method to identify aggregation-prone regions in protein sequences, achieving high accuracy in predicting these regions.

MATE-Pred predicts TCR-epitope binding affinity using multi-modal attention, outperforming baselines with +8.4% MCC and +5.5% AUC.

The paper reports a novel calicivirus found in an Indian bovine calf and highlights its divergence from known Neboviruses.

This paper introduces a computational pipeline to predict binding affinity of SARS-CoV-2 variants to hACE2 and neutralizing antibodies, showing Omicron variants have reduced binding to most RBD-directed antibodies.

This study predicts SARS-CoV-2 spike protein binding affinity to ACE2 orthologs across 299 vertebrate species, revealing broad host range and potential for cross-species transmission.