| On a simple approach for determining applicability domain of QSAR models K Roy, S Kar, P Ambure Chemometrics and Intelligent Laboratory Systems 145, 22-29, 2015 | 728 | 2015 |
| Be aware of error measures. Further studies on validation of predictive QSAR models K Roy, RN Das, P Ambure, RB Aher Chemometrics and Intelligent Laboratory Systems 152, 18-33, 2016 | 684 | 2016 |
| “NanoBRIDGES” software: open access tools to perform QSAR and nano-QSAR modeling P Ambure, RB Aher, A Gajewicz, T Puzyn, K Roy Chemometrics and Intelligent Laboratory Systems 147, 1-13, 2015 | 192 | 2015 |
| How important is to detect systematic error in predictions and understand statistical applicability domain of QSAR models? K Roy, P Ambure, RB Aher Chemometrics and Intelligent Laboratory Systems 162, 44-54, 2017 | 146 | 2017 |
| Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models? K Roy, P Ambure, S Kar, PK Ojha Journal of Chemometrics, e2992, 2018 | 124 | 2018 |
| Prediction reliability of QSAR models: an overview of various validation tools P De, S Kar, P Ambure, K Roy Archives of Toxicology 96 (5), 1279-1295, 2022 | 115 | 2022 |
| How precise are our quantitative structure–activity relationship derived predictions for new query chemicals? K Roy, P Ambure, S Kar ACS omega 3 (9), 11392-11406, 2018 | 106 | 2018 |
| QSAR-Co: an open source software for developing robust multitasking or multitarget classification-based QSAR models P Ambure, AK Halder, H Gonzalez Diaz, MNDS Cordeiro Journal of chemical information and modeling 59 (6), 2538-2544, 2019 | 103 | 2019 |
| The “double cross-validation” software tool for MLR QSAR model development K Roy, P Ambure Chemometrics and Intelligent Laboratory Systems 159, 108-126, 2016 | 87 | 2016 |
| Pharmacophore mapping-based virtual screening followed by molecular docking studies in search of potential acetylcholinesterase inhibitors as anti-Alzheimer's agents P Ambure, S Kar, K Roy Biosystems 116, 10-20, 2014 | 83 | 2014 |
| Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: an in silico approach P Ambure, J Bhat, T Puzyn, K Roy Journal of Biomolecular Structure and Dynamics 37 (5), 1282-1306, 2019 | 80 | 2019 |
| New workflow for QSAR model development from small data sets: Small dataset curator and small dataset modeler. Integration of data curation, exhaustive double cross-validation … P Ambure, A Gajewicz-Skretna, MNDS Cordeiro, K Roy Journal of chemical information and modeling 59 (10), 4070-4076, 2019 | 57 | 2019 |
| In vitro evaluation and in silico screening of synthetic acetylcholinesterase inhibitors bearing functionalized piperidine pharmacophores G Brahmachari, CY Choo, P Ambure, K Roy Bioorganic & Medicinal Chemistry 23 (15), 4567-4575, 2015 | 55 | 2015 |
| Turning deep-eutectic solvents into value-added products for CO2 capture: A desirability-based virtual screening study AK Halder, P Ambure, Y Perez-Castillo, MNDS Cordeiro Journal of CO2 Utilization 58, 101926, 2022 | 37 | 2022 |
| Understanding the structural requirements of cyclic sulfone hydroxyethylamines as hBACE1 inhibitors against Aβ plaques in Alzheimer's disease: a predictive QSAR approach P Ambure, K Roy RSC Advances 6 (34), 28171-28186, 2016 | 34 | 2016 |
| 3D-QSAR and molecular docking analysis of biphenyl amide derivatives as p38α mitogen-activated protein kinase inhibitors PS Ambure, RP Gangwal, AT Sangamwar Molecular diversity 16 (2), 377-388, 2012 | 31 | 2012 |
| Exploration of synthetic antioxidant flavonoid analogs as acetylcholinesterase inhibitors: An approach towards finding their quantitative structure–activity relationship A Karmakar, P Ambure, T Mallick, S Das, K Roy, NA Begum Medicinal Chemistry Research 28, 723-741, 2019 | 29 | 2019 |
| Advances in quantitative structure–activity relationship models of anti-Alzheimer’s agents P Ambure, K Roy Expert opinion on drug discovery 9 (6), 697-723, 2014 | 28 | 2014 |
| CADD modeling of multi-target drugs against Alzheimer's disease P Ambure, K Roy Current Drug Targets 18 (5), 522-533, 2017 | 25 | 2017 |
| Exploring structural requirements of leads for improving activity and selectivity against CDK5/p25 in Alzheimer's disease: an in silico approach P Ambure, K Roy RSC Advances 4 (13), 6702-6709, 2014 | 24 | 2014 |
KUNAL ROYProfessor, Jadavpur University, DTC Laboratory, Dept. Pharmaceutical Technology, IndiaВерификована је имејл адреса на jadavpuruniversity.in
