Characterizing the Chemical Space of ERK2 Kinase Inhibitors Using Descriptors Computed from Molecular Dynamics Trajectories. - Jeremy R. Ash; Denis Fourches (J. Chem. Inf. Model., 2017)

chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models. - Jeremy R. Ash; Jacqueline M. Hughes-Oliver (CoRR, 2018)

chemmodlab: a cheminformatics modeling laboratory R package for fitting and assessing machine learning models. - Jeremy R. Ash; Jacqueline M. Hughes-Oliver (J. Cheminformatics, 2018)

Confidence Bands and Hypothesis Test Methods for Recall and Precision Curves at Extremely Small Fractions with Applications to Drug Discovery. - Jeremy R. Ash; Jacqueline M. Hughes-Oliver (CoRR, 2019)

Cheminformatics approach to exploring and modeling trait-associated metabolite profiles. - Jeremy R. Ash; Mélaine A. Kuenemann; Daniel M. Rotroff; Alison A. Motsinger-Reif; Denis Fourches (J. Cheminformatics, 2019)

A Method for Controlling Extrapolation when Visualizing and Optimizing the Prediction Profiles of Statistical and Machine Learning Models. - Jeremy R. Ash; Laura Lancaster; Chris Gotwalt (CoRR, 2022)

Confidence bands and hypothesis tests for hit enrichment curves. - Jeremy R. Ash; Jacqueline M. Hughes-Oliver (J. Cheminformatics, 2022)

A call for an industry-led initiative to critically assess machine learning for real-world drug discovery. - Cas Wognum; Jeremy R. Ash; Matteo Aldeghi; Raquel Rodríguez-Pérez; Cheng Fang; Alan C. Cheng; Daniel J. Price; Djork-Arné Clevert; Ola Engkvist; W. Patrick Walters (Nat. Mac. Intell., 2024)