Sean Ekins

Development and Characterization of pFluor50, a Fluorogenic-Based Kinetic Assay System for High-Throughput Inhibition Screening and Characterization of Time-Dependent Inhibition and Inhibition Type for Six Human CYPs

Dual use of artificial-intelligence-powered drug discovery

Machine Learning Models Identify New Inhibitors for Human OATP1B1

Machine Learning Models Identify Inhibitors of SARS-CoV-2

Remdesivir and EIDD-1931 Interact with Human Equilibrative Nucleoside Transporters 1 and 2: Implications for Reaching SARS-CoV-2 Viral Sanctuary Sites

Déjà vu: Stimulating open drug discovery for SARS-CoV-2

Molecule Property Analyses of Active Compounds for <i>Mycobacterium tuberculosis</i>

Predicting Drug Interactions with Human Equilibrative Nucleoside Transporters 1 and 2 Using Functional Knockout Cell Lines and Bayesian Modeling

Exploiting machine learning for end-to-end drug discovery and development

The Natural Product Eugenol Is an Inhibitor of the Ebola Virus In Vitro

High-throughput screening and Bayesian machine learning for copper-dependent inhibitors of <i>Staphylococcus aureus</i>

New targets for HIV drug discovery

Comparing and Validating Machine Learning Models for <i>Mycobacterium tuberculosis</i> Drug Discovery

Assessment of Substrate-Dependent Ligand Interactions at the Organic Cation Transporter OCT2 Using Six Model Substrates

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets

A Phenotypic Based Target Screening Approach Delivers New Antitubercular CTP Synthetase Inhibitors

Addressing the Metabolic Stability of Antituberculars through Machine Learning

Non-classical transpeptidases yield insight into new antibacterials

Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of <i>Mycobacterium tuberculosis</i> Infection (2014–2015)

Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets

Machine Learning Models and Pathway Genome Data Base for Trypanosoma cruzi Drug Discovery

Thiophenecarboxamide Derivatives Activated by EthA Kill Mycobacterium tuberculosis by Inhibiting the CTP Synthetase PyrG

Evolution of a thienopyrimidine antitubercular relying on medicinal chemistry and metabolomics insights

Looking Back to the Future: Predicting <i>in Vivo</i> Efficacy of Small Molecules versus <i>Mycobacterium tuberculosis</i>

Are Bigger Data Sets Better for Machine Learning? Fusing Single-Point and Dual-Event Dose Response Data for <i>Mycobacterium tuberculosis</i>

Cross-reactivity studies and predictive modeling of “Bath Salts” and other amphetamine-type stimulants with amphetamine screening immunoassays

Enhancing Hit Identification in Mycobacterium tuberculosis Drug Discovery Using Validated Dual-Event Bayesian Models

Fusing Dual-Event Data Sets for <i>Mycobacterium tuberculosis</i> Machine Learning Models and Their Evaluation

Molecular Determinants of Ligand Selectivity for the Human Multidrug and Toxin Extruder Proteins MATE1 and MATE2-K

Novel diaryl ureas with efficacy in a mouse model of malaria