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ORCIDOlexandr Isayev
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2020 – today
- 2024
[j14]Kenneth M. Merz Jr.
, Yee-Siew Choong, Zoe Cournia, Olexandr Isayev, Thereza A. Soares, Guo-Wei Wei, Feng Zhu:
Editorial: Machine Learning in Materials Science. J. Chem. Inf. Model. 64(10): 3959-3960 (2024)- [c2]Jiayuan Chen, Kehan Guo, Zhen Liu, Olexandr Isayev, Xiangliang Zhang:
Uncertainty-Aware Yield Prediction with Multimodal Molecular Features. AAAI 2024: 8274-8282 - [c1]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. ICLR 2024 - 2023
- [j13]Filipp Gusev, Evgeny Gutkin, Maria G. Kurnikova, Olexandr Isayev:
Active Learning Guided Drug Design Lead Optimization Based on Relative Binding Free Energy Modeling. J. Chem. Inf. Model. 63(2): 583-594 (2023) - [i8]Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang:
Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks. CoRR abs/2310.00115 (2023) - [i7]Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Olexandr Isayev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Jr, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou:
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows. CoRR abs/2310.20155 (2023) - 2022
- [j12]Hatice Gokcan, Jirair K. Bedoyan, Olexandr Isayev:
Simulations of Pathogenic E1α Variants: Allostery and Impact on Pyruvate Dehydrogenase Complex-E1 Structure and Function. J. Chem. Inf. Model. 62(14): 3463-3475 (2022) - [j11]Zhen Liu, Tetiana Zubatiuk, Adrian E. Roitberg, Olexandr Isayev:
Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials. J. Chem. Inf. Model. 62(22): 5373-5382 (2022) - [j10]Mohit Pandey, Michael Fernández, Francesco Gentile, Olexandr Isayev, Alexander Tropsha, Abraham C. Stern, Artem Cherkasov:
The transformational role of GPU computing and deep learning in drug discovery. Nat. Mach. Intell. 4(3): 211-221 (2022) - 2021
- [j9]Marco Fronzi, Olexandr Isayev, David A. Winkler, Joseph George Shapter, Amanda V. Ellis, Peter C. Sherrell, Nick A. Shepelin, Alexander Corletto, Michael J. Ford:
Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures. Adv. Intell. Syst. 3(11): 2100080 (2021) - [j8]Farshad Firouzi, Bahareh J. Farahani, Mahmoud Daneshmand, Kathy Grise, Jaeseung Song, Roberto Saracco, Lucy Lu Wang, Kyle Lo, Plamen Angelov, Eduardo A. Soares, Po-Shen Loh, Zeynab Talebpour, Reza Moradi, Mohsen Goodarzi, Haleh Ashraf, Mohammad Talebpour, Alireza Talebpour, Luca Romeo, Rupam Das, Hadi Heidari, Dana K. Pasquale, James Moody, Chris Woods, Erich S. Huang, Payam M. Barnaghi, Majid Sarrafzadeh, Ron C. Li, Kristen L. Beck, Olexandr Isayev, NakMyoung Sung, Alan Luo:
Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World. IEEE Internet Things J. 8(16): 12826-12846 (2021) - [j7]Maria Korshunova, Boris Ginsburg, Alexander Tropsha, Olexandr Isayev:
OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design. J. Chem. Inf. Model. 61(1): 7-13 (2021) - [i6]Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer:
Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR abs/2112.03235 (2021) - 2020
- [j6]Xiang Gao, Farhad Ramezanghorbani, Olexandr Isayev, Justin S. Smith, Adrian E. Roitberg:
TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials. J. Chem. Inf. Model. 60(7): 3408-3415 (2020)
2010 – 2019
- 2019
- [j5]Sherif Farag, Rachel M. Bleich, Elizabeth A. Shank, Olexandr Isayev, Albert A Bowers, Alexander Tropsha:
Inter-Modular Linkers play a crucial role in governing the biosynthesis of non-ribosomal peptides. Bioinform. 35(19): 3584-3591 (2019) - [j4]Michael Fernández, Fuqiang Ban, Godwin Woo, Olexandr Isayev, Carl Perez, Valery Fokin, Alexander Tropsha, Artem Cherkasov:
Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects. J. Chem. Inf. Model. 59(4): 1306-1313 (2019) - [i5]Mariya Popova, Mykhailo Shvets, Junier Oliva, Olexandr Isayev:
MolecularRNN: Generating realistic molecular graphs with optimized properties. CoRR abs/1905.13372 (2019) - [i4]Marco Fronzi, Mutaz Abu Ghazaleh, Olexandr Isayev, David A. Winkler, Joe Shapter, Michael J. Ford:
Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery. CoRR abs/1911.11559 (2019) - 2018
- [i3]Justin S. Smith, Ben Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrian E. Roitberg:
Less is more: sampling chemical space with active learning. CoRR abs/1801.09319 (2018) - 2017
- [i2]Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg:
ANI-1: A data set of 20M off-equilibrium DFT calculations for organic molecules. CoRR abs/1708.04987 (2017) - [i1]Mariya Popova, Olexandr Isayev, Alexander Tropsha:
Deep Reinforcement Learning for De-Novo Drug Design. CoRR abs/1711.10907 (2017) - 2015
- [j3]Liudmyla K. Sviatenko, Olexandr Isayev, Leonid Gorb, Frances C. Hill, Danuta Leszczynska, Jerzy Leszczynski:
Are the reduction and oxidation properties of nitrocompounds dissolved in water different from those produced when adsorbed on a silica surface? A DFT M05-2X computational study. J. Comput. Chem. 36(14): 1029-1035 (2015) - 2011
- [j2]Liudmyla K. Sviatenko, Olexandr Isayev, Leonid Gorb, Frances Hill, Jerzy Leszczynski:
Toward robust computational electrochemical predicting the environmental fate of organic pollutants. J. Comput. Chem. 32(10): 2195-2203 (2011)
2000 – 2009
- 2007
- [j1]Olexandr Isayev, Leonid Gorb, Jerzy Leszczynski:
Theoretical calculations: Can Gibbs free energy for intermolecular complexes be predicted efficiently and accurately? J. Comput. Chem. 28(9): 1598-1609 (2007)
Coauthor Index
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