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Journal of Chemical Information and Modeling
|
August 18, 2023
FEP Protocol Builder: Optimization of Free Energy Perturbation Protocols Using Active Learning
César de Oliveira, Karl Leswing, Shulu Feng, et al.
Scientific Reports
|
October 11, 2023
Development of scalable and generalizable machine learned force field for polymers
Shaswat Mohanty, James Stevenson, Andrea R Browning, et al.
Journal of Chemical Theory and Computation
|
March 15, 2022
Transferable Neural Network Potential Energy Surfaces for Closed-Shell Organic Molecules: Extension to Ions
Leif D Jacobson, James M Stevenson, Farhad Ramezanghorbani, et al.
Journal of Chemical Theory and Computation
|
September 30, 2021
Efficient Exploration of Chemical Space with Docking and Deep Learning
Ying Yang, Kun Yao, Matthew P Repasky, et al.
Chemical Science
|
April 10, 2018
MoleculeNet: a benchmark for molecular machine learning
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, et al.
Frontiers in Chemistry
|
February 3, 2022
Design of Organic Electronic Materials With a Goal-Directed Generative Model Powered by Deep Neural Networks and High-Throughput Molecular Simulations
H Shaun Kwak, Yuling An, David J Giesen, et al.
Journal of Chemical Information and Modeling
|
June 3, 2020
Combining Cloud-Based Free-Energy Calculations, Synthetically Aware Enumerations, and Goal-Directed Generative Machine Learning for Rapid Large-Scale Chemical Exploration and Optimization
Phani Ghanakota, Pieter H Bos, Kyle D Konze, et al.
Journal of Chemical Information and Modeling
|
August 13, 2019
Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors
Kyle D Konze, Pieter H Bos, Markus K Dahlgren, et al.
The Journal of Physical Chemistry. B
|
August 16, 2022
High-Dimensional Neural Network Potential for Liquid Electrolyte Simulations
Steven Dajnowicz, Garvit Agarwal, James M Stevenson, et al.
The Journal of Physical Chemistry. A
|
August 19, 2022
<i>De Novo</i> Design of Molecules with Low Hole Reorganization Energy Based on a Quarter-Million Molecule DFT Screen: Part 2
Joshua Staker, Kyle Marshall, Karl Leswing, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Journal of Chemical Information and Modeling
|
August 18, 2023
FEP Protocol Builder: Optimization of Free Energy Perturbation Protocols Using Active Learning
César de Oliveira, Karl Leswing, Shulu Feng, et al.
Scientific Reports
|
October 11, 2023
Development of scalable and generalizable machine learned force field for polymers
Shaswat Mohanty, James Stevenson, Andrea R Browning, et al.
Journal of Chemical Theory and Computation
|
March 15, 2022
Transferable Neural Network Potential Energy Surfaces for Closed-Shell Organic Molecules: Extension to Ions
Leif D Jacobson, James M Stevenson, Farhad Ramezanghorbani, et al.
Journal of Chemical Theory and Computation
|
September 30, 2021
Efficient Exploration of Chemical Space with Docking and Deep Learning
Ying Yang, Kun Yao, Matthew P Repasky, et al.
Chemical Science
|
April 10, 2018
MoleculeNet: a benchmark for molecular machine learning
Zhenqin Wu, Bharath Ramsundar, Evan N Feinberg, et al.
Frontiers in Chemistry
|
February 3, 2022
Design of Organic Electronic Materials With a Goal-Directed Generative Model Powered by Deep Neural Networks and High-Throughput Molecular Simulations
H Shaun Kwak, Yuling An, David J Giesen, et al.
Journal of Chemical Information and Modeling
|
June 3, 2020
Combining Cloud-Based Free-Energy Calculations, Synthetically Aware Enumerations, and Goal-Directed Generative Machine Learning for Rapid Large-Scale Chemical Exploration and Optimization
Phani Ghanakota, Pieter H Bos, Kyle D Konze, et al.
Journal of Chemical Information and Modeling
|
August 13, 2019
Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors
Kyle D Konze, Pieter H Bos, Markus K Dahlgren, et al.
The Journal of Physical Chemistry. B
|
August 16, 2022
High-Dimensional Neural Network Potential for Liquid Electrolyte Simulations
Steven Dajnowicz, Garvit Agarwal, James M Stevenson, et al.
The Journal of Physical Chemistry. A
|
August 19, 2022
<i>De Novo</i> Design of Molecules with Low Hole Reorganization Energy Based on a Quarter-Million Molecule DFT Screen: Part 2
Joshua Staker, Kyle Marshall, Karl Leswing, et al.
Page
of 2