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Connor W Coley

Showing results (91-100 of 113) with videos related to

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Chemical Science|February 13, 2019
A graph-convolutional neural network model for the prediction of chemical reactivityConnor W Coley, Wengong Jin, Luke Rogers, et al.
Digital Discovery|December 12, 2024
Rapid prediction of conformationally-dependent DFT-level descriptors using graph neural networks for carboxylic acids and alkyl aminesBrittany C Haas, Melissa A Hardy, Shree Sowndarya S V, et al.
Journal of Chemical Information and Modeling|May 10, 2022
Machine Learning on DNA-Encoded Library Count Data Using an Uncertainty-Aware Probabilistic Loss FunctionKatherine S Lim, Andrew G Reidenbach, Bruce K Hua, et al.
ACS Central Science|January 1, 2024
Dataset Design for Building Models of Chemical ReactivityPriyanka Raghavan, Brittany C Haas, Madeline E Ruos, et al.
Chemical Science|June 24, 2021
Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptorsYanfei Guan, Connor W Coley, Haoyang Wu, et al.
Journal of the American Chemical Society|May 20, 2024
Incorporating Synthetic Accessibility in Drug Design: Predicting Reaction Yields of Suzuki Cross-Couplings by Leveraging AbbVie's 15-Year Parallel Library Data SetPriyanka Raghavan, Alexander J Rago, Pritha Verma, et al.
Natural Product Reports|August 16, 2024
Empowering natural product science with AI: leveraging multimodal data and knowledge graphsDavid Meijer, Mehdi A Beniddir, Connor W Coley, et al.
Journal of the American Chemical Society|November 2, 2021
The Open Reaction DatabaseSteven M Kearnes, Michael R Maser, Michael Wleklinski, et al.
ACS Central Science|March 30, 2026
Higher-Level Strategies for Computer-Aided RetrosynthesisJihye Roh, Joonyoung F Joung, Kevin Yu, et al.
ACS Central Science|October 2, 2019
BigSMILES: A Structurally-Based Line Notation for Describing MacromoleculesTzyy-Shyang Lin, Connor W Coley, Hidenobu Mochigase, et al.
Pageof 12

Showing results (91-100 of 113) with videos related to

Sort By:
Pageof 12
Chemical Science|February 13, 2019
A graph-convolutional neural network model for the prediction of chemical reactivityConnor W Coley, Wengong Jin, Luke Rogers, et al.
Digital Discovery|December 12, 2024
Rapid prediction of conformationally-dependent DFT-level descriptors using graph neural networks for carboxylic acids and alkyl aminesBrittany C Haas, Melissa A Hardy, Shree Sowndarya S V, et al.
Journal of Chemical Information and Modeling|May 10, 2022
Machine Learning on DNA-Encoded Library Count Data Using an Uncertainty-Aware Probabilistic Loss FunctionKatherine S Lim, Andrew G Reidenbach, Bruce K Hua, et al.
ACS Central Science|January 1, 2024
Dataset Design for Building Models of Chemical ReactivityPriyanka Raghavan, Brittany C Haas, Madeline E Ruos, et al.
Chemical Science|June 24, 2021
Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptorsYanfei Guan, Connor W Coley, Haoyang Wu, et al.
Journal of the American Chemical Society|May 20, 2024
Incorporating Synthetic Accessibility in Drug Design: Predicting Reaction Yields of Suzuki Cross-Couplings by Leveraging AbbVie's 15-Year Parallel Library Data SetPriyanka Raghavan, Alexander J Rago, Pritha Verma, et al.
Natural Product Reports|August 16, 2024
Empowering natural product science with AI: leveraging multimodal data and knowledge graphsDavid Meijer, Mehdi A Beniddir, Connor W Coley, et al.
Journal of the American Chemical Society|November 2, 2021
The Open Reaction DatabaseSteven M Kearnes, Michael R Maser, Michael Wleklinski, et al.
ACS Central Science|March 30, 2026
Higher-Level Strategies for Computer-Aided RetrosynthesisJihye Roh, Joonyoung F Joung, Kevin Yu, et al.
ACS Central Science|October 2, 2019
BigSMILES: A Structurally-Based Line Notation for Describing MacromoleculesTzyy-Shyang Lin, Connor W Coley, Hidenobu Mochigase, et al.
Pageof 12