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Plos One
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July 30, 2013
Prediction errors in learning drug response from gene expression data - influence of labeling, sample size, and machine learning algorithm
Immanuel Bayer, Philip Groth, Sebastian Schneckener
BMC Medical Genomics
|
October 15, 2011
Quantifying stability in gene list ranking across microarray derived clinical biomarkers
Sebastian Schneckener, Nilou S Arden, Andreas Schuppert
Archives of Toxicology
|
October 9, 2020
A workflow to build PBTK models for novel species
Sebastian Schneckener, Thomas G Preuss, Lars Kuepfer, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals
|
February 2, 2012
Using expression data for quantification of active processes in physiologically based pharmacokinetic modeling
Michaela Meyer, Sebastian Schneckener, Bernd Ludewig, et al.
Journal of Chemical Information and Modeling
|
May 3, 2018
Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water
Anna Theresa Cavasin, Alexander Hillisch, Felix Uellendahl, et al.
Plos One
|
March 22, 2018
Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits
Panteleimon D Mavroudis, Helen E Hermes, Donato Teutonico, et al.
Computational Biology and Chemistry
|
July 21, 2010
An elastic network model to identify characteristic stress response genes
Sebastian Schneckener, Linus Görlitz, Heidrun Ellinger-Ziegelbauer, et al.
Journal of Pharmaceutical Sciences
|
November 4, 2024
Prediction of human pharmacokinetics from chemical structure: combining mechanistic modeling with machine learning
Andrea Gruber, Florian Führer, Stephan Menz, et al.
Journal of Computer-Aided Molecular Design
|
January 31, 2024
A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat
Florian Führer, Andrea Gruber, Holger Diedam, et al.
Journal of Chemical Information and Modeling
|
November 13, 2019
Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters
Sebastian Schneckener, Sergio Grimbs, Jessica Hey, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 13) with videos related to
Sort By:
Page
of 2
Plos One
|
July 30, 2013
Prediction errors in learning drug response from gene expression data - influence of labeling, sample size, and machine learning algorithm
Immanuel Bayer, Philip Groth, Sebastian Schneckener
BMC Medical Genomics
|
October 15, 2011
Quantifying stability in gene list ranking across microarray derived clinical biomarkers
Sebastian Schneckener, Nilou S Arden, Andreas Schuppert
Archives of Toxicology
|
October 9, 2020
A workflow to build PBTK models for novel species
Sebastian Schneckener, Thomas G Preuss, Lars Kuepfer, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals
|
February 2, 2012
Using expression data for quantification of active processes in physiologically based pharmacokinetic modeling
Michaela Meyer, Sebastian Schneckener, Bernd Ludewig, et al.
Journal of Chemical Information and Modeling
|
May 3, 2018
Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water
Anna Theresa Cavasin, Alexander Hillisch, Felix Uellendahl, et al.
Plos One
|
March 22, 2018
Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits
Panteleimon D Mavroudis, Helen E Hermes, Donato Teutonico, et al.
Computational Biology and Chemistry
|
July 21, 2010
An elastic network model to identify characteristic stress response genes
Sebastian Schneckener, Linus Görlitz, Heidrun Ellinger-Ziegelbauer, et al.
Journal of Pharmaceutical Sciences
|
November 4, 2024
Prediction of human pharmacokinetics from chemical structure: combining mechanistic modeling with machine learning
Andrea Gruber, Florian Führer, Stephan Menz, et al.
Journal of Computer-Aided Molecular Design
|
January 31, 2024
A deep neural network: mechanistic hybrid model to predict pharmacokinetics in rat
Florian Führer, Andrea Gruber, Holger Diedam, et al.
Journal of Chemical Information and Modeling
|
November 13, 2019
Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters
Sebastian Schneckener, Sergio Grimbs, Jessica Hey, et al.
Page
of 2