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Sebastian Mika

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

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Combinatorial Chemistry & High Throughput Screening|June 13, 2009
How wrong can we get? A review of machine learning approaches and error barsAnton Schwaighofer, Timon Schroeter, Sebastian Mika, et al.
Journal of Chemical Information and Modeling|April 6, 2005
Classifying 'drug-likeness' with kernel-based learning methodsKlaus-Robert Müller, Gunnar Rätsch, Sören Sonnenburg, et al.
Journal of Chemical Information and Modeling|May 14, 2009
Bias-correction of regression models: a case study on hERG inhibitionKatja Hansen, Fabian Rathke, Timon Schroeter, et al.
Molecular Pharmaceutics|July 20, 2007
Machine learning models for lipophilicity and their domain of applicabilityTimon Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
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 Computer-Aided Molecular Design|December 7, 2007
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery moleculesTimon Sebastian Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
Journal of Computer-Aided Molecular Design|July 17, 2007
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery moleculesTimon Sebastian Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
Chemmedchem|June 20, 2007
Predicting lipophilicity of drug-discovery molecules using Gaussian process modelsTimon S Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
Journal of Chemical Information and Modeling|January 25, 2007
Accurate solubility prediction with error bars for electrolytes: a machine learning approachAnton Schwaighofer, Timon Schroeter, Sebastian Mika, 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.
Pageof 1

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

Sort By:
Pageof 1
Combinatorial Chemistry & High Throughput Screening|June 13, 2009
How wrong can we get? A review of machine learning approaches and error barsAnton Schwaighofer, Timon Schroeter, Sebastian Mika, et al.
Journal of Chemical Information and Modeling|April 6, 2005
Classifying 'drug-likeness' with kernel-based learning methodsKlaus-Robert Müller, Gunnar Rätsch, Sören Sonnenburg, et al.
Journal of Chemical Information and Modeling|May 14, 2009
Bias-correction of regression models: a case study on hERG inhibitionKatja Hansen, Fabian Rathke, Timon Schroeter, et al.
Molecular Pharmaceutics|July 20, 2007
Machine learning models for lipophilicity and their domain of applicabilityTimon Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
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 Computer-Aided Molecular Design|December 7, 2007
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery moleculesTimon Sebastian Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
Journal of Computer-Aided Molecular Design|July 17, 2007
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery moleculesTimon Sebastian Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
Chemmedchem|June 20, 2007
Predicting lipophilicity of drug-discovery molecules using Gaussian process modelsTimon S Schroeter, Anton Schwaighofer, Sebastian Mika, et al.
Journal of Chemical Information and Modeling|January 25, 2007
Accurate solubility prediction with error bars for electrolytes: a machine learning approachAnton Schwaighofer, Timon Schroeter, Sebastian Mika, 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.
Pageof 1