Sean Ekins

According to our database, Sean Ekins authored at least 35 papers between 2001 and 2024.

Collaborative distances:

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

2024

Sequential Contrastive and Deep Learning Models to Identify Selective Butyrylcholinesterase Inhibitors.

Mustafa Kemal Ozalp, Patricia A. Vignaux, Ana C. Puhl, Thomas R. Lane, Fabio Urbina, Sean Ekins

J. Chem. Inf. Model., 2024

Near-Term Quantum Classification Algorithms Applied to Antimalarial Drug Discovery.

Matthew A. Dorsey, Kelvin Dsouza, Dhruv Ranganath, Joshua S. Harris, Thomas R. Lane, Fabio Urbina, Sean Ekins

J. Chem. Inf. Model., 2024

2023

Preventing AI From Creating Biochemical Threats.

Fabio Urbina, Filippa Lentzos, Cédric Invernizzi, Sean Ekins

J. Chem. Inf. Model., February, 2023

2022

A teachable moment for dual-use.

Fabio Urbina, Filippa Lentzos, Cédric Invernizzi, Sean Ekins

Nat. Mach. Intell., 2022

Dual use of artificial-intelligence-powered drug discovery.

Fabio Urbina, Filippa Lentzos, Cédric Invernizzi, Sean Ekins

Nat. Mach. Intell., 2022

Discovery of New Zika Protease and Polymerase Inhibitors through the Open Science Collaboration Project OpenZika.

Melina Mottin, Bruna Katiele de Paula Sousa, Nathalya Cristina de Moraes Roso Mesquita, Ketllyn Irene Zagato de Oliveira, Gabriela Dias Noske, Geraldo Rodrigues Sartori, Aline Albuquerque, Fabio Urbina, Ana C. Puhl, José Teófilo Moreira-Filho, Guilherme E. Souza, Rafael V. C. Guido, Eugene N. Muratov, Bruno Junior Neves, João Herminio Martins Da Silva, Alex E. Clark, Jair L. Siqueira-Neto, Alexander L. Perryman, Glaucius Oliva, Sean Ekins, Carolina Horta Andrade

J. Chem. Inf. Model., 2022

2021

Defending Antiviral Cationic Amphiphilic Drugs That May Cause Drug-Induced Phospholipidosis.

Thomas R. Lane, Sean Ekins

J. Chem. Inf. Model., 2021

Machine Learning Models Identify Inhibitors of SARS-CoV-2.

Victor O. Gawriljuk, Phyo Phyo Kyaw Zin, Ana C. Puhl, Kimberley M. Zorn, Daniel H. Foil, Thomas R. Lane, Brett Hurst, Tatyana Almeida Tavella, Fabio Trindade Maranhão Costa, Premkumar Lakshmanane, Jean Bernatchez, Andre S. Godoy, Glaucius Oliva, Jair L. Siqueira-Neto, Peter B. Madrid, Sean Ekins

J. Chem. Inf. Model., 2021

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

Victor O. Gawriljuk, Daniel H. Foil, Ana C. Puhl, Kimberley M. Zorn, Thomas R. Lane, Olga Riabova, Vadim Makarov, Andre S. Godoy, Glaucius Oliva, Sean Ekins

J. Chem. Inf. Model., 2021

Quantum Machine Learning Algorithms for Drug Discovery Applications.

Kushal Batra, Kimberley M. Zorn, Daniel H. Foil, Eni Minerali, Victor O. Gawriljuk, Thomas R. Lane, Sean Ekins

J. Chem. Inf. Model., 2021

2017

The new alchemy: Online networking, data sharing and research activity distribution tools for scientists.

Antony J. Williams, Lou Peck, Sean Ekins

F1000Research, 2017

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

Open Source Bayesian Models. 3. Composite Models for Prediction of Binned Responses.

Alex M. Clark, Krishna Dole, Sean Ekins

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. 2. Mining a "Big Dataset" To Create and Validate Models with ChEMBL.

Alex M. Clark, Sean Ekins

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

Machines first, humans second: on the importance of algorithmic interpretation of open chemistry data.

Alex M. Clark, Antony J. Williams, Sean Ekins

J. Cheminformatics, 2015

Modeling error in experimental assays using the bootstrap principle: understanding discrepancies between assays using different dispensing technologies.

Sonya M. Hanson, Sean Ekins, John D. Chodera

J. Comput. Aided Mol. Des., 2015

Finding small molecules for the 'next Ebola'.

Sean Ekins, Christopher Southan, Megan Coffee

F1000Research, 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

Ten Simple Rules of Live Tweeting at Scientific Conferences.

Sean Ekins, Ethan O. Perlstein

PLoS Comput. Biol., 2014

Computational Prediction and Validation of an Expert's Evaluation of Chemical Probes.

Nadia K. Litterman, Christopher A. Lipinski, Barry A. Bunin, Sean Ekins

J. Chem. Inf. Model., 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

Using cheminformatics to predict cross reactivity of "designer drugs" to their currently available immunoassays.

Matthew D. Krasowski, Sean Ekins

J. Cheminformatics, 2014

New target prediction and visualization tools incorporating open source molecular fingerprints for TB Mobile 2.0.

Alex M. Clark, Malabika Sarker, Sean Ekins

J. Cheminformatics, 2014

Bigger data, collaborative tools and the future of predictive drug discovery.

Sean Ekins, Alex M. Clark, S. Joshua Swamidass, Nadia K. Litterman, Antony J. Williams

J. Comput. Aided Mol. Des., 2014

Collaboration for rare disease drug discovery research.

Nadia K. Litterman, Michele Rhee, David C. Swinney, Sean Ekins

F1000Research, 2014

2013

Discovery of Novel Antimalarial Compounds Enabled by QSAR-Based Virtual Screening.

Liying Zhang, Denis Fourches, Alexander Sedykh, Hao Zhu, Alexander Golbraikh, Sean Ekins, Julie Clark, Michele C. Connelly, Martina Sigal, Dena Hodges, Armand Guiguemde, R. Kiplin Guy, Alexander Tropsha

J. Chem. Inf. Model., 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

TB mobile: a mobile app for anti-tuberculosis molecules with known targets.

Sean Ekins, Alex M. Clark, Malabika Sarker

J. Cheminformatics, 2013

2012

Why Open Drug Discovery Needs Four Simple Rules for Licensing Data and Models.

Antony J. Williams, John Wilbanks, Sean Ekins

PLoS Comput. Biol., 2012

2009

Challenges Predicting Ligand-Receptor Interactions of Promiscuous Proteins: The Nuclear Receptor PXR.

Sean Ekins, Sandhya Kortagere, Manisha Iyer, Erica J. Reschly, Markus A. Lill, Matthew R. Redinbo, Matthew D. Krasowski

PLoS Comput. Biol., 2009

2002

Towards a new age of virtual ADME/TOX and multidimensional drug discovery.

Sean Ekins, Bruno Boulanger, Peter W. Swaan, Maggie A. Z. Hupcey

J. Comput. Aided Mol. Des., 2002

2001

Three-Dimensional Quantitative Structure-Permeability Relationship Analysis for a Series of Inhibitors of Rhinovirus Replication.

Sean Ekins, Gregory L. Durst, Robert E. Stratford, David A. Thorner, Richard A. Lewis, Richard J. Loncharich, James H. Wikel

J. Chem. Inf. Comput. Sci., 2001