| Water dynamics at protein–protein interfaces: Molecular dynamics study of virus–host receptor complexes P Dutta, M Botlani, S Varma The Journal of Physical Chemistry B 118 (51), 14795-14807, 2014 | 26 | 2014 |
| The disruption of prenylation leads to pleiotropic rearrangements in cellular behavior in Staphylococcus aureus CN Krute, RK Carroll, FE Rivera, A Weiss, RM Young, A Shilling, ... Molecular microbiology 95 (5), 819-832, 2015 | 23 | 2015 |
| Modeling the Yield Strength of Hot Strip Low Carbon Steels by Artificial Neural Network MB Esfahani, MR Toroghinejad, AR Key Yeganeh Materials & Design 30 (9), 6, 2009 | 22 | 2009 |
| Effect of intrinsic and extrinsic factors on the simulated D‐band length of type I collagen S Varma, M Botlani, JR Hammond, HL Scott, JPRO Orgel, JD Schieber Proteins: Structure, Function, and Bioinformatics 83 (10), 1800-1812, 2015 | 21 | 2015 |
| Artificial Neural Network Modeling the Tensile Strength of Hot Strip Mill Products MB Esfahani, MR Toroghinejad, S Abbasi ISIJ International 49 (10), 5, 2009 | 21 | 2009 |
| Machine learning approaches to evaluate correlation patterns in allosteric signaling: A case study of the PDZ2 domain M Botlani, A Siddiqui, S Varma The Journal of Chemical Physics 148 (24), 2018 | 17 | 2018 |
| Stimulation of Nipah Fusion: Small Intradomain Changes Trigger Extensive Interdomain Rearrangements SV Priyanka Dutta, Ahnaf Siddiqui, Mohsen Botlani Biophysical Journal 111 (8), 1621-1630, 2016 | 10 | 2016 |
| Discerning intersecting fusion‐activation pathways in the Nipah virus using machine learning S Varma, M Botlani, RE Leighty Proteins: Structure, Function, and Bioinformatics 82 (12), 3241-3254, 2014 | 10 | 2014 |
| Application of Bayesian Neural Networks to Predict Strength and Grain Size of Hot Strip Low Carbon Steels MR Toroghinejad, MB Esfahani INTECH Open Access Publisher, 2011 | 5 | 2011 |
| Incorporation of multi-state information improves molecular modelling of dynamic allostery: a case study of PDZ domains computational quantitative characterization of entropic … M Botlani, S Varma Biophysical Journal 112 (3), 496a, 2017 | 1 | 2017 |
| Allosteric regulation of nipah virus entry into host cells S Varma, P Dutta, M Botlani Biophysical Journal 108 (2), 363a, 2015 | 1 | 2015 |
| Application of a Bayesian Artificial Neural Network and the Reversible Jump Markov Chain Monte Carlo Method to predict the grain size of hot strip low carbon steels M Botlani-Esfahani, MR Toroghinejad J. Serb. Chem. Soc 77 (7), 937-944, 2012 | 1 | 2012 |
| Application of a Bayesian Artificial Neural Network and the Reversible Jump Markov Chain Monte Carlo Method to predict the grain size of hot strip low carbon steels M Botlani-Esfahani, MR Toroghinejad J. Serb. Chem. Soc 77 (7), 937-944, 2012 | 1 | 2012 |
| Application of Bayesian ANN and RJMCMC to predict the grain size of hot strip low carbon steels M Botlani-Esfahani, RM Toroghinejad Journal of the Serbian Chemical Society 77 (7), 937-944, 2012 | 1 | 2012 |
| Machine learning enabled approach to incorporate multi-state information in molecular modeling of dynamic allostery: A case study of the PDZ2 domain M Botlani, A Siddiqui, S Varma ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 254, 2017 | | 2017 |
| Modeling of Dynamic Allostery in Proteins Enabled by Machine Learning M Botlani University of South Florida, 2017 | | 2017 |
| Quantifying Conformational Ensemble Changes in Proteins Using Inverse Machine Learning M Botlani, A Siddiqui, S Varma Intelligent Systems for Molecular Biology(ISCB) 2016, 2016 | | 2016 |
| Elucidating Ephrin-Induced Intersecting Signaling Pathways in the Nipah Virus G Protein using Machine Learning M Botlani, R Leighty, S Varma Biophysical Journal 106 (2), 409a, 2014 | | 2014 |
| Tuesday, February 10, 2015 363a S Varma, P Dutta, M Botlani | | |
Prof. Mohammad Reza ToroghinejadDepartment of Materials Engineering, Isfahan University of Technology, Isfahan, IranVerified email at iut.ac.ir
