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Jacob Gerlach

Showing results (1-10 of 6) with videos related to

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Drug Discovery Today|September 12, 2022
Combining DELs and machine learning for toxicology predictionVincent Blay, Xiaoyu Li, Jacob Gerlach, et al.
Pharmaceutical Research|July 24, 2019
Repurposing Approved Drugs as Inhibitors of K<sub>v</sub>7.1 and Na<sub>v</sub>1.8 to Treat Pitt Hopkins SyndromeSean Ekins, Jacob Gerlach, Kimberley M Zorn, et al.
Molecular Pharmaceutics|October 21, 2022
Machine Learning Models Identify New Inhibitors for Human OATP1B1Thomas R Lane, Fabio Urbina, Xiaohong Zhang, et al.
Chemical Research in Toxicology|February 3, 2023
Validation of Acetylcholinesterase Inhibition Machine Learning Models for Multiple SpeciesPatricia A Vignaux, Thomas R Lane, Fabio Urbina, et al.
Communications Chemistry|June 12, 2024
The Goldilocks paradigm: comparing classical machine learning, large language models, and few-shot learning for drug discovery applicationsScott H Snyder, Patricia A Vignaux, Mustafa Kemal Ozalp, et al.
Molecular Pharmaceutics|December 29, 2021
Machine Learning Models for <i>Mycobacterium tuberculosis</i><i>In Vitro</i> Activity: Prediction and Target VisualizationThomas R Lane, Fabio Urbina, Laura Rank, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Drug Discovery Today|September 12, 2022
Combining DELs and machine learning for toxicology predictionVincent Blay, Xiaoyu Li, Jacob Gerlach, et al.
Pharmaceutical Research|July 24, 2019
Repurposing Approved Drugs as Inhibitors of K<sub>v</sub>7.1 and Na<sub>v</sub>1.8 to Treat Pitt Hopkins SyndromeSean Ekins, Jacob Gerlach, Kimberley M Zorn, et al.
Molecular Pharmaceutics|October 21, 2022
Machine Learning Models Identify New Inhibitors for Human OATP1B1Thomas R Lane, Fabio Urbina, Xiaohong Zhang, et al.
Chemical Research in Toxicology|February 3, 2023
Validation of Acetylcholinesterase Inhibition Machine Learning Models for Multiple SpeciesPatricia A Vignaux, Thomas R Lane, Fabio Urbina, et al.
Communications Chemistry|June 12, 2024
The Goldilocks paradigm: comparing classical machine learning, large language models, and few-shot learning for drug discovery applicationsScott H Snyder, Patricia A Vignaux, Mustafa Kemal Ozalp, et al.
Molecular Pharmaceutics|December 29, 2021
Machine Learning Models for <i>Mycobacterium tuberculosis</i><i>In Vitro</i> Activity: Prediction and Target VisualizationThomas R Lane, Fabio Urbina, Laura Rank, et al.
Pageof 1