Similarity Searching in Files of Three-Dimensional Chemical Structures: Analysis of the BIOSTER Database Using Two-Dimensional Fingerprints and Molecular Field Descriptors. - Ansgar Schuffenhauer; Valerie J. Gillet; Peter Willett 002 (J. Chem. Inf. Comput. Sci., 2000)

An Ontology for Pharmaceutical Ligands and Its Application for in Silico Screening and Library Design. - Ansgar Schuffenhauer; Jürg Zimmermann; Ruedi Stoop; Jan-Jan van der Vyver; Steffano Lecchini; Edgar Jacoby (J. Chem. Inf. Comput. Sci., 2002)

Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins. - Ansgar Schuffenhauer; Philipp Floersheim; Pierre Acklin; Edgar Jacoby (J. Chem. Inf. Comput. Sci., 2003)

Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures. - Jérôme Hert; Peter Willett 002; David J. Wilton; Pierre Acklin; Kamal Azzaoui; Edgar Jacoby; Ansgar Schuffenhauer (J. Chem. Inf. Model., 2004)

Sequential Superparamagnetic Clustering for Unbiased Classification of High-Dimensional Chemical Data. - Thomas Ott; Albert Kern; Ansgar Schuffenhauer; Maxim Popov; Pierre Acklin; Edgar Jacoby; Ruedi Stoop (J. Chem. Inf. Model., 2004)

Introducing the Consensus Modeling Concept in Genetic Algorithms: Application to Interpretable Discriminant Analysis. - Milan Ganguly; Nathan Brown; Ansgar Schuffenhauer; Peter Ertl; Valerie J. Gillet; Paulette A. Greenidge (J. Chem. Inf. Model., 2006)

New Methods for Ligand-Based Virtual Screening: Use of Data Fusion and Machine Learning to Enhance the Effectiveness of Similarity Searching. - Jérôme Hert; Peter Willett 002; David J. Wilton; Pierre Acklin; Kamal Azzaoui; Edgar Jacoby; Ansgar Schuffenhauer (J. Chem. Inf. Model., 2006)

Relationships between Molecular Complexity, Biological Activity, and Structural Diversity. - Ansgar Schuffenhauer; Nathan Brown; Paul Selzer; Peter Ertl; Edgar Jacoby (J. Chem. Inf. Model., 2006)

Clustering and Rule-Based Classifications of Chemical Structures Evaluated in the Biological Activity Space. - Ansgar Schuffenhauer; Nathan Brown; Peter Ertl; Jeremy L. Jenkins; Paul Selzer; Jacques Hamon (J. Chem. Inf. Model., 2007)

The Scaffold Tree - Visualization of the Scaffold Universe by Hierarchical Scaffold Classification. - Ansgar Schuffenhauer; Peter Ertl; Silvio Roggo; Stefan Wetzel; Marcus A. Koch; Herbert Waldmann (J. Chem. Inf. Model., 2007)

Natural Product-likeness Score and Its Application for Prioritization of Compound Libraries. - Peter Ertl; Silvio Roggo; Ansgar Schuffenhauer (J. Chem. Inf. Model., 2008)

Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions. - Peter Ertl; Ansgar Schuffenhauer (J. Cheminformatics, 2009)

Compound Set Enrichment: A Novel Approach to Analysis of Primary HTS Data. - Thibault Varin; Hanspeter Gubler; Christian N. Parker; Ji-Hu Zhang; Pichai Raman; Peter Ertl; Ansgar Schuffenhauer (J. Chem. Inf. Model., 2010)

MultiMCS: A Fast Algorithm for the Maximum Common Substructure Problem on Multiple Molecules. - Ramesh Hariharan; Anand Janakiraman; Ramaswamy Nilakantan; Bhupender Singh; Sajith Varghese; Gregory A. Landrum; Ansgar Schuffenhauer (J. Chem. Inf. Model., 2011)

Mining for Bioactive Scaffolds with Scaffold Networks: Improved Compound Set Enrichment from Primary Screening Data. - Thibault Varin; Ansgar Schuffenhauer; Peter Ertl; Steffen Renner (J. Chem. Inf. Model., 2011)

Splitting chemical structure data sets for federated privacy-preserving machine learning. - Jaak Simm; Lina Humbeck; Adam Zalewski; Noé Sturm; Wouter Heyndrickx; Yves Moreau; Bernd Beck; Ansgar Schuffenhauer (J. Cheminformatics, 2021)

Industry-Scale Orchestrated Federated Learning for Drug Discovery. - Martijn Oldenhof; Gergely Ács; Balázs Pejó; Ansgar Schuffenhauer; Nicholas Holway; Noé Sturm; Arne Dieckmann; Oliver Fortmeier; Eric Boniface; Clément Mayer; Arnaud Gohier; Peter Schmidtke; et al. (CoRR, 2022)

Industry-Scale Orchestrated Federated Learning for Drug Discovery. - Martijn Oldenhof; Gergely Ács; Balázs Pejó; Ansgar Schuffenhauer; Nicholas Holway; Noé Sturm; Arne Dieckmann; Oliver Fortmeier; Eric Boniface; Clément Mayer; Arnaud Gohier; Peter Schmidtke; et al. (AAAI, 2023)

MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information. - Wouter Heyndrickx; Lewis H. Mervin; Tobias Morawietz; Noé Sturm; Lukas Friedrich; Adam Zalewski; Anastasia Pentina; Lina Humbeck; Martijn Oldenhof; Ritsuya Niwayama; Peter Schmidtke; Nikolas Fechner; et al. (J. Chem. Inf. Model., 2024)