Jonathan Goodman

Professor of Chemistry

University of Cambridge

United Kingdom

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Jonathan Goodman is a Professor of Chemistry at the University of Cambridge, UK. His research areas encompass computational organic chemistry, machine learning applications in toxicity characterization, and developing strategies for catalysis in organic reactions. His recent publications include topics on C–H borylation selectivity and molecular identification techniques.

Articles (20)

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2024

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2022

Collaborators (4)

Jolene Reid

Assistant Professor

The University of British Columbia

CANADA

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Kerstin von Borries

Technical University of Denmark

DENMARK

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Andrew Bond

University of Cambridge

UNITED KINGDOM

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Alexei Lapkin

University of Cambridge

UNITED KINGDOM

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Jonathan Goodman

Research Interests

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About

Articles (20)

Introduction to Computational Organic Chemistry

Suppressing Cis/Trans ‘Ring-Flipping’ in Organoaluminium(III)-2-Pyridyl Dimers–Design Strategies Towards Lewis Acid Catalysts for Alkene Oligomerisation

Leveraging Language Model Multitasking To Predict C–H Borylation Selectivity

Leveraging Language Model Multitasking To Predict C-H Borylation Selectivity

Suppressing <i>Cis</i>/<i>Trans</i> 'Ring-Flipping' in Organoaluminium(III)-2-Pyridyl Dimers-Design Strategies Towards Lewis Acid Catalysts for Alkene Oligomerisation

Every atom counts: predicting sites of reaction based on chemistry within two bonds

HSQC Spectra Simulation and Matching for Molecular Identification

HSQC Spectra Simulation and Matching for Molecular Identification

CONFPASS: Fast DFT Re-Optimizations of Structures from Conformation Searches

CONFPASS: Fast DFT Re-Optimizations of Structures from Conformation Searches

Selective Functionalisation of 5‐Methylcytosine by Organic Photoredox Catalysis

Selective Functionalisation of 5‐Methylcytosine by Organic Photoredox Catalysis

Selective Functionalisation of 5-Methylcytosine by Organic Photoredox Catalysis

Quantitative In Silico Prediction of the Rate of Protodeboronation by a Mechanistic Density Functional Theory-Aided Algorithm

Quantitative In Silico Prediction of the Rate of Protodeboronation by a Mechanistic Density Functional Theory-Aided Algorithm

Interpreting vibrational circular dichroism spectra: the Cai•factor for absolute configuration with confidence

Potential for Machine Learning to Address Data Gaps in Human Toxicity and Ecotoxicity Characterization

Potential for Machine Learning to Address Data Gaps in Human Toxicity and Ecotoxicity Characterization

A review of molecular representation in the age of machine learning

Analysing a billion reactions with the RInChI

Collaborators (4)

Jolene Reid

Kerstin von Borries

Andrew Bond

Alexei Lapkin

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