Antonius ter Laak

According to our database, Antonius ter Laak authored at least 10 papers between 2007 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Large-scale evaluation of k-fold cross-validation ensembles for uncertainty estimation.

Thomas-Martin Dutschmann, Lennart Kinzel, Antonius ter Laak, Knut Baumann

J. Cheminformatics, December, 2023

2019

Mechanistic Reactivity Descriptors for the Prediction of Ames Mutagenicity of Primary Aromatic Amines.

Lara Kuhnke, Antonius ter Laak, Andreas H. Göller

J. Chem. Inf. Model., 2019

2017

Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors.

Marc van Dijk, Antonius ter Laak, Jörg D. Wichard, Luigi Capoferri, Nico P. E. Vermeulen, Daan P. Geerke

J. Chem. Inf. Model., September, 2017

Efficiency of different measures for defining the applicability domain of classification models.

Waldemar Klingspohn, Miriam Mathea, Antonius ter Laak, Nikolaus Heinrich, Knut Baumann

J. Cheminformatics, 2017

2010

A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test.

Johannes Mohr, Brijnesh J. Jain, Andreas Sutter, Antonius ter Laak, Thomas Steger-Hartmann, Nikolaus Heinrich, Klaus Obermayer

J. Chem. Inf. Model., 2010

2009

Benchmark Data Set for in Silico Prediction of Ames Mutagenicity.

Katja Hansen, Sebastian Mika, Timon Schroeter, Andreas Sutter, Antonius ter Laak, Thomas Steger-Hartmann, Nikolaus Heinrich, Klaus-Robert Müller

J. Chem. Inf. Model., 2009

2008

A Probabilistic Approach to Classifying Metabolic Stability.

Anton Schwaighofer, Timon Schroeter, Sebastian Mika, Katja Hansen, Antonius ter Laak, Philip Lienau, Andreas Reichel, Nikolaus Heinrich, Klaus-Robert Müller

J. Chem. Inf. Model., 2008

Binding site detection via mutual information.

Jörg D. Wichard, Ronald Kühne, Antonius ter Laak

Proceedings of the FUZZ-IEEE 2008, 2008

2007

Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach.

Anton Schwaighofer, Timon Schroeter, Sebastian Mika, Julian Laub, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller

J. Chem. Inf. Model., 2007

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

Timon Schroeter, Anton Schwaighofer, Sebastian Mika, Antonius ter Laak, Detlev Sülzle, Ursula Ganzer, Nikolaus Heinrich, Klaus-Robert Müller

J. Comput. Aided Mol. Des., 2007