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GEN Biotechnology|November 6, 2023
Generative Artificial Intelligence-Assisted Protein Design Must Consider Repurposing PotentialSean Ekins, Maximilian Brackmann, Cédric Invernizzi, et al.
Chemical Biology & Drug Design|November 24, 2018
A rapid method for estimation of the efficacy of potential antimicrobials in humans and animals by agar diffusion assayElena G Salina, Sean Ekins, Vadim A Makarov
Journal of Chemical Information and Modeling|June 27, 2014
Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosisSean Ekins, Joel S Freundlich, Robert C Reynolds
Cold Spring Harbor Perspectives in Medicine|November 3, 2025
Tuberculosis Drug Discovery in the Age of Artificial IntelligenceSean Ekins, Thomas R Lane, Jason T Wong
Journal of Chemical Information and Modeling|January 25, 2023
Preventing AI From Creating Biochemical ThreatsFabio Urbina, Filippa Lentzos, Cédric Invernizzi, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals|September 17, 2010
A predictive ligand-based Bayesian model for human drug-induced liver injurySean Ekins, Antony J Williams, Jinghai J Xu
Drug Discovery Today|May 5, 2010
Evolving molecules using multi-objective optimization: applying to ADME/ToxSean Ekins, J Dana Honeycutt, James T Metz
Molecular Informatics|December 1, 2012
Open Drug Discovery Teams: A Chemistry Mobile App for CollaborationSean Ekins, Alex M Clark, Antony J Williams
Drug Discovery Today|August 24, 2013
Multifaceted roles of ultra-rare and rare disease patients/parents in drug discoveryJill Wood, Lori Sames, Allison Moore, et al.
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