Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Olexandr Isayev

Showing results (71-80 of 93) with videos related to

Pageof 10
Sort By:
The Journal of Chemical Physics|September 15, 2023
Synergy of semiempirical models and machine learning in computational chemistryNikita Fedik, Benjamin Nebgen, Nicholas Lubbers, et al.
The Journal of Physical Chemistry Letters|July 25, 2018
Discovering a Transferable Charge Assignment Model Using Machine LearningAndrew E Sifain, Nicholas Lubbers, Benjamin T Nebgen, et al.
Journal of Molecular Modeling|May 31, 2012
Validation of a novel secretion modification region (SMR) of HIV-1 Nef using cohort sequence analysis and molecular modelingPatrick E Campbell, Olexandr Isayev, Syed A Ali, et al.
Crystal Growth & Design|November 10, 2025
Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network PotentialsKamal Singh Nayal, Dana O'Connor, Roman Zubatyuk, et al.
Angewandte Chemie (International Ed. in English)|July 13, 2025
Design of Tough 3D Printable Elastomers with Human-in-the-Loop Reinforcement LearningJohann L Rapp, Dylan M Anstine, Filipp Gusev, et al.
RSC Advances|May 11, 2022
Adsorption of nitrogen-containing compounds on hydroxylated α-quartz surfacesOksana Tsendra, A Daniel Boese, Olexandr Isayev, et al.
Communications Chemistry|January 25, 2023
Generative and reinforcement learning approaches for the automated de novo design of bioactive compoundsMaria Korshunova, Niles Huang, Stephen Capuzzi, et al.
Nature Reviews. Chemistry|April 28, 2023
Extending machine learning beyond interatomic potentials for predicting molecular propertiesNikita Fedik, Roman Zubatyuk, Maksim Kulichenko, et al.
Nature Chemistry|March 7, 2024
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potentialShuhao Zhang, Małgorzata Z Makoś, Ryan B Jadrich, et al.
Nature Communications|October 17, 2025
AQuaRef: machine learning accelerated quantum refinement of protein structuresRoman Zubatyuk, Malgorzata Biczysko, Kavindri Ranasinghe, et al.
Pageof 10

Showing results (71-80 of 93) with videos related to

Sort By:
Pageof 10
The Journal of Chemical Physics|September 15, 2023
Synergy of semiempirical models and machine learning in computational chemistryNikita Fedik, Benjamin Nebgen, Nicholas Lubbers, et al.
The Journal of Physical Chemistry Letters|July 25, 2018
Discovering a Transferable Charge Assignment Model Using Machine LearningAndrew E Sifain, Nicholas Lubbers, Benjamin T Nebgen, et al.
Journal of Molecular Modeling|May 31, 2012
Validation of a novel secretion modification region (SMR) of HIV-1 Nef using cohort sequence analysis and molecular modelingPatrick E Campbell, Olexandr Isayev, Syed A Ali, et al.
Crystal Growth & Design|November 10, 2025
Efficient Molecular Crystal Structure Prediction and Stability Assessment with AIMNet2 Neural Network PotentialsKamal Singh Nayal, Dana O'Connor, Roman Zubatyuk, et al.
Angewandte Chemie (International Ed. in English)|July 13, 2025
Design of Tough 3D Printable Elastomers with Human-in-the-Loop Reinforcement LearningJohann L Rapp, Dylan M Anstine, Filipp Gusev, et al.
RSC Advances|May 11, 2022
Adsorption of nitrogen-containing compounds on hydroxylated α-quartz surfacesOksana Tsendra, A Daniel Boese, Olexandr Isayev, et al.
Communications Chemistry|January 25, 2023
Generative and reinforcement learning approaches for the automated de novo design of bioactive compoundsMaria Korshunova, Niles Huang, Stephen Capuzzi, et al.
Nature Reviews. Chemistry|April 28, 2023
Extending machine learning beyond interatomic potentials for predicting molecular propertiesNikita Fedik, Roman Zubatyuk, Maksim Kulichenko, et al.
Nature Chemistry|March 7, 2024
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potentialShuhao Zhang, Małgorzata Z Makoś, Ryan B Jadrich, et al.
Nature Communications|October 17, 2025
AQuaRef: machine learning accelerated quantum refinement of protein structuresRoman Zubatyuk, Malgorzata Biczysko, Kavindri Ranasinghe, et al.
Pageof 10