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Angewandte Chemie (International Ed. in English)|April 26, 2016
From Complex Natural Products to Simple Synthetic Mimetics by Computational De Novo DesignLukas Friedrich, Tiago Rodrigues, Claudia S Neuhaus, et al.Chemmedchem|April 22, 2018
Designing Anticancer Peptides by Constructive Machine LearningFrancesca Grisoni, Claudia S Neuhaus, Gisela Gabernet, et al.Journal of Molecular Modeling|April 7, 2019
De novo design of anticancer peptides by ensemble artificial neural networksFrancesca Grisoni, Claudia S Neuhaus, Miyabi Hishinuma, et al.Journal of Medicinal Chemistry|May 31, 2023
De Novo Design of Nurr1 Agonists via Fragment-Augmented Generative Deep Learning in Low-Data RegimeMarco Ballarotto, Sabine Willems, Tanja Stiller, et al.Current Opinion in Structural Biology|February 4, 2023
Chemical language models for de novo drug design: Challenges and opportunitiesFrancesca GrisoniNature Communications|January 7, 2023
Leveraging molecular structure and bioactivity with chemical language models for de novo drug designMichael Moret, Irene Pachon Angona, Leandro Cotos, et al.Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|June 27, 2021
Learning from Nature: From a Marine Natural Product to Synthetic Cyclooxygenase-1 Inhibitors by Automated De Novo DesignLukas Friedrich, Gino Cingolani, Ying-Hui Ko, et al.Journal of Medicinal Chemistry|September 26, 2014
Extending the structure-activity relationship of anthranilic acid derivatives as farnesoid X receptor modulators: development of a highly potent partial farnesoid X receptor agonistDaniel Merk, Christina Lamers, Khalil Ahmad, et al.Alzheimer'S & Dementia (New York, N. Y.)|March 26, 2024
Baricitinib and tofacitinib off-target profile, with a focus on Alzheimer's diseaseMaria L Faquetti, Laura Slappendel, Hélène Bigonne, et al.Digital Discovery|December 27, 2024
A hitchhiker's guide to deep chemical language processing for bioactivity predictionRıza Özçelik, Francesca GrisoniPageof 49