Kimberley M. Zorn

发表

Machine Learning Platform to Discover Novel Growth Inhibitors of Neisseria gonorrhoeae

Sean Ekins, Janaina Cruz Pereira, Samer S. Daher, 2020, Pharmaceutical Research.

Machine Learning Models Identify Inhibitors of SARS-CoV-2

Thomas Rogers, Sean Ekins, Kimberley M. Zorn, 2020, bioRxiv.

Quantum Machine Learning Algorithms for Drug Discovery Applications

Sean Ekins, Kimberley M. Zorn, Victor O. Gawriljuk, 2021, J. Chem. Inf. Model..

Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus

Sean Ekins, Kimberley M. Zorn, Glaucius Oliva, 2021, J. Chem. Inf. Model..

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

Sean Ekins, Christopher Southan, Kimberley M. Zorn, 2020, Drug Discovery Today.

Synergistic drug combinations and machine learning for drug repurposing in chordoma

Tammy M. Havener, Kimberley M. Zorn, Daniel H. Foil, 2020, Scientific Reports.

Ebola Virus Bayesian Machine Learning Models Enable New in Vitro Leads

Kimberley M. Zorn, Joel S. Freundlich, Peter B. Madrid, 2019, ACS omega.

High-throughput screening and Bayesian machine learning for copper-dependent inhibitors of Staphylococcus aureus.

Kimberley M. Zorn, Nichole A. Tower, S. Ekins, 2019, Metallomics : integrated biometal science.

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

Alex M. Clark, Sean Ekins, Kimberley M. Zorn, 2018, Molecular Pharmacology.

Developing Next Generation Tools for Computational Toxicology

Alex M. Clark, Sean Ekins, Kimberley M. Zorn, 2018 .

Dispirotripiperazine-core compounds, their biological activity with a focus on broad antiviral property, and perspectives in drug design (mini-review)

Kimberley M. Zorn, S. Ekins, V. Makarov, 2020, European Journal of Medicinal Chemistry.

A Very Large-Scale Bioactivity Comparison of Deep Learning and Multiple Machine Learning Algorithms for Drug Discovery

Kimberley M. Zorn, Daniel H. Foil, S. Ekins, 2020 .

Comparing the Pfizer Central Nervous System Multiparameter Optimization Calculator and a BBB Machine Learning Model.

Kimberley M. Zorn, S. Ekins, Fabio L. Urbina, 2021, ACS chemical neuroscience.

Computational Approaches to Identify Molecules Binding to Mycobacterium tuberculosis KasA

Kimberley M. Zorn, Joel S. Freundlich, Patricia A. Vignaux, 2020, ACS omega.

Repurposing Approved Drugs as Inhibitors of Kv7.1 and Nav1.8 to Treat Pitt Hopkins Syndrome

Kimberley M. Zorn, S. Ekins, Brett M. Antonio, 2019, Pharmaceutical Research.

Evaluation of Assay Central Machine Learning Models for Rat Acute Oral Toxicity Prediction

Kimberley M. Zorn, Daniel H. Foil, S. Ekins, 2020 .

Drug Discovery and Development for Kinetoplastid Diseases

Kimberley M. Zorn, Daniel H. Foil, S. Ekins, 2021 .

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

Sean Ekins, Ana C Puhl, Kimberley M Zorn, 2019, Nature Materials.

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

Kimberley M. Zorn, Daniel H. Foil, C. Southan, 2020, Drug Discovery Today.

High Throughput and Computational Repurposing for Neglected Diseases

Kimberley M. Zorn, S. Ekins, C. Andrade, 2018, Pharmaceutical Research.

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

Kimberley M. Zorn, Daniel H. Foil, S. Ekins, 2020, Molecular Pharmacology.

Multiple Machine Learning Comparisons of HIV Cell-based and Reverse Transcriptase Data Sets.

Sean Ekins, Kimberley M Zorn, Thomas R Lane, 2019, Molecular pharmaceutics.

Multiple approaches to repurposing drugs for neuroblastoma.

Tammy M. Havener, Kimberley M. Zorn, Daniel H. Foil, 2022, Bioorganic & medicinal chemistry.

CATMoS: Collaborative Acute Toxicity Modeling Suite

Kimberley M. Zorn, Daniel P. Russo, Timothy E. H. Allen, 2021, Environmental health perspectives.

Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

Sean Ekins, Kimberley M Zorn, Daniel P Russo, 2018, Molecular pharmaceutics.

Comparison of Machine Learning Models for the Androgen Receptor.

Sean Ekins, Thomas R Lane, Kimberley M. Zorn, 2020, Environmental science & technology.

Comparing Machine Learning Models for Aromatase (P450 19A1).

Sean Ekins, Thomas R Lane, Kimberley M. Zorn, 2020, Environmental science & technology.

Machine Learning Models for Estrogen Receptor Bioactivity and Endocrine Disruption Prediction.

Sean Ekins, Kimberley M Zorn, Thomas R Lane, 2020, Environmental science & technology.

Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.

Hao Zhu, Sean Ekins, Kimberley M Zorn, 2018, Molecular pharmaceutics.

Flavonoids from Pterogyne nitens as Zika virus NS2B-NS3 protease inhibitors.

Kimberley M. Zorn, S. Ekins, C. Andrade, 2021, Bioorganic chemistry.

A Machine Learning Strategy for Drug Discovery Identifies Anti-Schistosomal Small Molecules

Kimberley M. Zorn, Cecelia L. McConnon, Daniel H. Foil, 2021, ACS infectious diseases.

Chalcones from Angelica keiskei (ashitaba) inhibit key Zika virus replication proteins.

Kimberley M. Zorn, Daniel H. Foil, S. Ekins, 2022, Bioorganic chemistry.

Bioactivity Comparison across Multiple Machine Learning Algorithms Using over 5000 Datasets for Drug Discovery.

Sean Ekins, Thomas R Lane, Kimberley M. Zorn, 2020, Molecular pharmaceutics.

Mycobacterium abscessus drug discovery using machine learning.

Kimberley M. Zorn, S. Ekins, M. Braunstein, 2022, Tuberculosis.

Multiple Computational Approaches for Predicting Drug Interactions with Human Equilibrative Nucleoside Transporter 1

Kimberley M. Zorn, S. Ekins, S. Wright, 2021, Drug Metabolism and Disposition.

Halogen Substitution Influences Ketamine Metabolism by Cytochrome P450 2B6: In Vitro and Computational Approaches.

Kimberley M. Zorn, S. Ekins, E. Kharasch, 2018, Molecular pharmaceutics.

Cationic Compounds with SARS-CoV-2 Antiviral Activity and Their Interaction with Organic Cation Transporter/Multidrug and Toxin Extruder Secretory Transporters

Kimberley M. Zorn, S. Ekins, S. Wright, 2021, The Journal of Pharmacology and Experimental Therapeutics.

Response to Comments on “Remdesivir and EIDD-1931 Interact with Human Equilibrative Nucleoside Transporters 1 and 2: Implications for Reaching SARS-CoV-2 Viral Sanctuary Sites”

Kimberley M. Zorn, S. Ekins, S. Wright, 2022, Molecular Pharmacology.

Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1

Jennifer J Klein, Kimberley M. Zorn, Nancy C. Baker, 2021, ACS omega.

Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Stephen P. Boyd, Kimberley M. Zorn, Daniel P. Russo, 2021, Environmental health perspectives.

Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI).

Sean Ekins, Kimberley M Zorn, Thomas R Lane, 2020, Molecular pharmaceutics.

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

Kimberley M. Zorn, S. Ekins, S. Wright, 2021, Molecular Pharmacology.

High Throughput and Computational Repurposing for Neglected Diseases

Sean Ekins, Kimberley M. Zorn, Carolina Horta Andrade, 2018, Pharmaceutical Research.

High-Throughput Phenotypic Screening and Machine Learning Methods Enabled the Selection of Broad-Spectrum Low-Toxicity Antitrypanosomatidic Agents

Kimberley M. Zorn, Daniel H. Foil, S. Ekins, 2023, Journal of medicinal chemistry.