Professor of Chemistry
We use chemical informatics, computational chemistry, machine learning and AI to investigate molecules and to discover more about their structure, reactivity, analytical data and properties.
(Full list of publications)
Professor Goodman discusses his research
Publications
MolE8: finding DFT potential energy surface minima values from force-field optimised organic molecules with new machine learning representations
Chemical Science
(2022)
13
7204
(doi: 10.1039/d1sc06324c)
Analysing a Billion Reactions with the RInChI
Pure and Applied Chemistry
(2022)
94
643
(doi: 10.1515/pac-2021-2008)
Towards quantifying the uncertainty in in silico predictions using Bayesian learning
Computational Toxicology
(2022)
23
100228
(doi: 10.1016/j.comtox.2022.100228)
RSC CICAG Open Chemical Science Meeting: integrating chemical data from two symposia and a series of workshops
Pure and Applied Chemistry
(2022)
94
677
(doi: 10.1515/pac-2021-1003)
The DP5 probability, quantification and visualisation of structural uncertainty in single molecules
Chemical Science
(2022)
13
3507
(doi: 10.1039/d1sc04406k)
The DP5 Probability, Quantification and Visualisation of Structural Uncertainty in Single Molecules
(2022)
A review of molecular representation in the age of machine learning
WIREs Computational Molecular Science
(2022)
12
e1603
(doi: 10.1002/wcms.1603)
Computational insights on the origin of enantioselectivity in reactions with diarylprolinol silyl ether catalysts via a radical pathway
Organic Chemistry Frontiers
(2022)
9
3730
(doi: 10.1039/d2qo00354f)
Correction: Computational insights on the origin of enantioselectivity in reactions with diarylprolinol silyl ether catalysts via a radical pathway (Organic Chemistry Frontiers (2022) DOI: 10.1039/d2qo00354f)
Organic Chemistry Frontiers
(2022)
9
4221
(doi: 10.1039/d2qo90045a)
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