Modelling and mutation studies on the histamine H1-receptor agonist binding site reveal different binding modes for H1-agonists: Asp116 (TM3) has a constitutive role in receptor stimulation. - Antonius ter Laak; Hendrik Timmerman; Rob Leurs; Paul H. J. Nederkoorn; Martine J. Smit; Gabriëlle M. Donné-Op den Kelder (J. Comput. Aided Mol. Des., 1995)

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)

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)

Binding site detection via mutual information. - Jörg D. Wichard; Ronald Kühne; Antonius ter Laak (FUZZ-IEEE, 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)

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)

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)

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)

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., 2017)

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)

Large-scale evaluation of k-fold cross-validation ensembles for uncertainty estimation. - Thomas-Martin Dutschmann; Lennart Kinzel; Antonius ter Laak; Knut Baumann (J. Cheminformatics, 2023)