Localization and quantification of hydrophobicity: The molecular free energy density (MolFESD) concept and its application to sweetness recognition. - Robert Jäger; K. Friedemann Schmidt; Bernd Schilling; Jürgen Brickmann (J. Comput. Aided Mol. Des., 2000)

Prediction of tautomer ratios by embedded-cluster integral equation theory. - Stefan M. Kast; Jochen Heil; Stefan Güssregen; K. Friedemann Schmidt (J. Comput. Aided Mol. Des., 2010)

Erratum to: Prediction of tautomer ratios by embedded-cluster integral equation theory. - Stefan M. Kast; Jochen Heil; Stefan Güssregen; K. Friedemann Schmidt (J. Comput. Aided Mol. Des., 2010)

Phototoxicity - from molecular descriptors to classification models. - K. Friedemann Schmidt; Andreas Evers; Alexander Amberg; Gerhard Hessler; Catherine Robles; Karl-Heinz Baringhaus (J. Cheminformatics, 2011)

3D-QSAR Based on Quantum-Chemical Molecular Fields: Toward an Improved Description of Halogen Interactions. - Stefan Güssregen; Hans Matter; Gerhard Hessler; Marco Müller 002; K. Friedemann Schmidt; Timothy Clark (J. Chem. Inf. Model., 2012)

The SAMPL5 challenge for embedded-cluster integral equation theory: solvation free energies, aqueous pK a, and cyclohexane-water log D. - Nicolas Tielker; Daniel Tomazic; Jochen Heil; Thomas Kloss; Sebastian Ehrhart; Stefan Güssregen; K. Friedemann Schmidt; Stefan M. Kast (J. Comput. Aided Mol. Des., 2016)

Predictive Multitask Deep Neural Network Models for ADME-Tox Properties: Learning from Large Data Sets. - Jan Wenzel; Hans Matter; K. Friedemann Schmidt (J. Chem. Inf. Model., 2019)

Quantum-mechanical property prediction of solvated drug molecules: what have we learned from a decade of SAMPL blind prediction challenges? - Nicolas Tielker; Lukas Eberlein; Gerhard Hessler; K. Friedemann Schmidt; Stefan Güssregen; Stefan M. Kast (J. Comput. Aided Mol. Des., 2021)

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment. - Inass Soukarieh; Gerhard Hessler; Hervé Minoux; Marcel Mohr; K. Friedemann Schmidt; Jan Wenzel; Pierre Barbillon; Hugo Gangloff; Pierre Gloaguen (CoRR, 2024)

Data-driven federated learning in drug discovery with knowledge distillation. - Thierry Hanser; Ernst Ahlberg; Alexander Amberg; Lennart T. Anger; Chris Barber; Richard J. Brennan; Alessandro Brigo; Annie Delaunois; Susanne Glowienke; Nigel Greene; Laura Johnston; Daniel Kuhn; et al. (Nat. Mac. Intell., 2025)