Joel S. Freundlich

According to our database, Joel S. Freundlich authored at least 7 papers between 2013 and 2016.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2016

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

Sean Ekins, Alexander L. Perryman, Alex M. Clark, Robert C. Reynolds, Joel S. Freundlich

J. Chem. Inf. Model., 2016

2015

A Virtual Screen Discovers Novel, Fragment-Sized Inhibitors of <i>Mycobacterium tuberculosis</i> InhA.

Alexander L. Perryman, Weixuan Yu, Xin Wang, Sean Ekins, Stefano Forli, Shao-Gang Li, Joel S. Freundlich, Peter J. Tonge, Arthur J. Olson

J. Chem. Inf. Model., 2015

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

Alex M. Clark, Krishna Dole, Anna Coulon-Spektor, Andrew M. McNutt, George Grass, Joel S. Freundlich, Robert C. Reynolds, Sean Ekins

J. Chem. Inf. Model., 2015

Machine learning models identify molecules active against the Ebola virus <i>in vitro</i>.

Sean Ekins, Joel S. Freundlich, Alex M. Clark, Manu Anantpadma, Robert A. Davey, Peter B. Madrid

F1000Research, 2015

2014

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

Sean Ekins, Richard Pottorf, Robert C. Reynolds, Antony J. Williams, Alex M. Clark, Joel S. Freundlich

J. Chem. Inf. Model., 2014

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

Sean Ekins, Joel S. Freundlich, Robert C. Reynolds

J. Chem. Inf. Model., 2014

2013

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

Sean Ekins, Joel S. Freundlich, Robert C. Reynolds

J. Chem. Inf. Model., 2013