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Katja Hansen

Showing results (11-20 of 17) with videos related to

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Journal of Chemical Information and Modeling|August 26, 2009
Benchmark data set for in silico prediction of Ames mutagenicityKatja Hansen, Sebastian Mika, Timon Schroeter, et al.
Journal of Chemical Information and Modeling|March 11, 2008
A probabilistic approach to classifying metabolic stabilityAnton Schwaighofer, Timon Schroeter, Sebastian Mika, et al.
Journal of Chemical Theory and Computation|November 20, 2015
Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization EnergiesKatja Hansen, Grégoire Montavon, Franziska Biegler, et al.
Bioorganic & Medicinal Chemistry Letters|March 30, 2010
Truxillic acid derivatives act as peroxisome proliferator-activated receptor gamma activatorsRamona Steri, Matthias Rupp, Ewgenij Proschak, et al.
Chemmedchem|January 1, 2010
From machine learning to natural product derivatives that selectively activate transcription factor PPARgammaMatthias Rupp, Timon Schroeter, Ramona Steri, et al.
Proceedings of the National Academy of Sciences of the United States of America|February 14, 2023
Planet-compatible pathways for transitioning the chemical industryFanran Meng, Andreas Wagner, Alexandre B Kremer, et al.
Journal of Chemical Information and Modeling|November 2, 2010
Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity setIurii Sushko, Sergii Novotarskyi, Robert Körner, et al.
Pageof 2

Showing results (11-20 of 17) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 17 results.
Journal of Chemical Information and Modeling|August 26, 2009
Benchmark data set for in silico prediction of Ames mutagenicityKatja Hansen, Sebastian Mika, Timon Schroeter, et al.
Journal of Chemical Information and Modeling|March 11, 2008
A probabilistic approach to classifying metabolic stabilityAnton Schwaighofer, Timon Schroeter, Sebastian Mika, et al.
Journal of Chemical Theory and Computation|November 20, 2015
Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization EnergiesKatja Hansen, Grégoire Montavon, Franziska Biegler, et al.
Bioorganic & Medicinal Chemistry Letters|March 30, 2010
Truxillic acid derivatives act as peroxisome proliferator-activated receptor gamma activatorsRamona Steri, Matthias Rupp, Ewgenij Proschak, et al.
Chemmedchem|January 1, 2010
From machine learning to natural product derivatives that selectively activate transcription factor PPARgammaMatthias Rupp, Timon Schroeter, Ramona Steri, et al.
Proceedings of the National Academy of Sciences of the United States of America|February 14, 2023
Planet-compatible pathways for transitioning the chemical industryFanran Meng, Andreas Wagner, Alexandre B Kremer, et al.
Journal of Chemical Information and Modeling|November 2, 2010
Applicability domains for classification problems: Benchmarking of distance to models for Ames mutagenicity setIurii Sushko, Sergii Novotarskyi, Robert Körner, et al.
Pageof 2