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Journal Article
S. Bapat, Viswanadh, N., Mujahid, M., Shirazi, A. Nasrolahi, Tiwari, R., Parang, K., Karthikeyan, M., Muthukrishnan, M., and Vyas, R., Synthesis, biological evaluation and molecular modeling studies of novel chromone/Aza-chromone fused α-aminophosphonates as Src kinase inhibitors, Journal of Scientific and Industrial Research, vol. 78, no. 2, pp. 111-117, 2019.
R. Vyas, Bapat, S., Jain, E., Tambe, S. S., Karthikeyan, M., and Kulkarni, B. D., Study of applications of machine learning based classification methods for virtual screening of lead molecules, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 7, pp. 658-672, 2015.
N. Shaikh, Bapat, S., Karthikeyan, M., and Vyas, R., Review on computational analysis of big data in breast cancer for predicting potential biomarkers, Current Topics in Medicinal Chemistry, vol. 22, no. 21, pp. 1793-1810, 2022.
V. Nalla, Shaikh, A., Bapat, S., Vyas, R., Karthikeyan, M., Yogeeswari, P., Sriram, D., and Muthukrishnan, M., Identification of potent chromone embedded [1,2,3]-triazoles as novel anti-tubercular agents, Royal Society Open Science, vol. 5, no. 4, p. Article Number: 171750, 2018.
P. Goel, Bapat, S., Vyas, R., Tambe, A., and Tambe, S. S., Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices, Journal of Chromatography A, vol. 1420, pp. 98-109, 2015.
S. Bapat, Vyas, R., and Karthikeyan, M., Exploring energy profiles of protein-protein interactions (PPIs) Using DFT method, Letters in Drug Design & Discovery, vol. 16, no. 6, pp. 670-677, 2019.
M. Karthikeyan, Nimje, D., Pahujani, R., Tyagi, K., Bapat, S., Vyas, R., and Padmakumar, K. Pillai, Chemoinformatics approach for building molecular networks from marine organisms, Combinatorial Chemistry & High Throughput Screening, vol. 18, no. 7, pp. 673-684, 2015.
R. Vyas, Bapat, S., Jain, E., Karthikeyan, M., Tambe, S., and Kulkarni, B. D., Building and analysis of protein-protein interactions related to diabetes mellitus using support vector machine, biomedical text mining and network analysis, Computational Biology and Chemistry, vol. 65, pp. 37-44, 2016.
R. Vyas, Bapat, S., Goel, P., Karthikeyan, M., Tambe, S. S., and Kulkarni, B. D., Application of genetic programming (GP) formalism for building disease predictive models from protein-protein interactions (PPI) data, IEEE-ACM Transactions on Computational Biology and Bioinformatics, vol. 15, no. 1, pp. 27-37, 2018.