Prediction of the Bonding State of Cysteine Residues in Proteins with Machine-Learning Methods. - Castrense Savojardo; Piero Fariselli; Pier Luigi Martelli; Priyank Shukla; Rita Casadio (CIBB, 2010)

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins. - Priyank Shukla (2010)

Hardware acceleration of genomics data analysis: challenges and opportunities. - Tony Robinson; Jim Harkin; Priyank Shukla (Bioinform., 2021)

Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity. - Bodhayan Prasad; Anthony J. Bjourson; Priyank Shukla (Briefings Bioinform., 2022)

Immuno-informatics analysis predicts B and T cell consensus epitopes for designing peptide vaccine against SARS-CoV-2 with 99.82% global population coverage. - Priyank Shukla; Preeti Pandey; Bodhayan Prasad; Tony Robinson; Rituraj Purohit; Leon G. D'cruz; Murtaza M. Tambuwala; Ankur Mutreja; Jim Harkin; Taranjit Singh Rai; Elaine K. Murray; David S. Gibson; et al. (Briefings Bioinform., 2022)

ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients. - Bodhayan Prasad; Cathy M. McGeough; Amanda Eakin; Tan Ahmed; Dawn Small; Philip Gardiner; Adrian Pendleton; Gary Wright; Anthony J. Bjourson; David S. Gibson; Priyank Shukla (PLoS Comput. Biol., 2022)