Professor in 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
Machine learning in predictive toxicology: recent applications and future directions for classification models
– Chem Res Toxicol
(2020)
34,
217
Confidence in Inactive and Active Predictions from Structural Alerts.
– Chemical Research in Toxicology
(2020)
33,
3010
A Computational and Experimental Investigation of the Origin of Selectivity in the Chiral Phosphoric Acid Catalyzed Enantioselective Minisci Reaction.
– Journal of the American Chemical Society
(2020)
142,
21091
(doi: 10.1021/jacs.0c09668)
Synergism of anisotropic and computational NMR methods reveals the likely configuration of phormidolide A.
– Chemical communications (Cambridge, England)
(2020)
56,
7565
(doi: 10.1039/d0cc03055d)
Neural network activation similarity: a new measure to assist decision making in chemical toxicology.
– Chemical Science
(2020)
11,
7335
(doi: 10.1039/d0sc01637c)
In Silico Guidance for in Vitro Androgen and Glucocorticoid Receptor ToxCast Assays
– Environmental science & technology
(2020)
54,
7461
(doi: 10.1021/acs.est.0c01105)
Synergism of anisotropic and computational NMR methods reveals the likely configuration of phormidolide A
– Chemical Communications
(2020)
(doi: 10.1039/d0cc03055d)
Rapid Route-Finding for Bifurcating Organic Reactions.
– J Am Chem Soc
(2020)
142,
9210
(doi: 10.1021/jacs.9b13449)
Charge-assisted phosph(v)azane anion receptors
– Dalton Trans
(2020)
49,
3403
(doi: 10.1039/d0dt00489h)
DP4-AI automated NMR data analysis: straight from spectrometer to structure.
– Chemical science
(2020)
11,
4351
(doi: 10.1039/d0sc00442a)
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