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Analytical Chemistry|February 13, 2024
Generating Molecular Fragmentation Graphs with Autoregressive Neural NetworksSamuel Goldman, Janet Li, Connor W ColeyJournal of Chemical Information and Modeling|September 19, 2023
MIST-CF: Chemical Formula Inference from Tandem Mass SpectraSamuel Goldman, Jiayi Xin, Joules Provenzano, et al.Plos Computational Biology|February 10, 2022
Machine learning modeling of family wide enzyme-substrate specificity screensSamuel Goldman, Ria Das, Kevin K Yang, et al.Journal of Chemical Information and Modeling|September 29, 2021
EHreact: Extended Hasse Diagrams for the Extraction and Scoring of Enzymatic Reaction TemplatesEsther Heid, Samuel Goldman, Karthik Sankaranarayanan, et al.ACS Central Science|September 2, 2021
Evidential Deep Learning for Guided Molecular Property Prediction and DiscoveryAva P Soleimany, Alexander Amini, Samuel Goldman, et al.Chemical Science|August 3, 2022
A focus on simulation and machine learning as complementary tools for chemical space navigationMatteo Aldeghi, Connor W ColeyChemical Science|October 24, 2022
A graph representation of molecular ensembles for polymer property predictionMatteo Aldeghi, Connor W ColeyJournal of Chemical Information and Modeling|July 26, 2022
Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction PredictionZhengkai Tu, Connor W ColeyThe Journal of Chemical Physics|March 2, 2022
Quantum chemistry-augmented neural networks for reactivity prediction: Performance, generalizability, and explainabilityThijs Stuyver, Connor W ColeyJournal of Chemical Information and Modeling|April 7, 2020
The Synthesizability of Molecules Proposed by Generative ModelsWenhao Gao, Connor W ColeyPageof 14