Beware of Unreliable Q2! A Comparative Study of Regression Metrics for Predictivity Assessment of QSAR Models. - Roberto Todeschini; Davide Ballabio; Francesca Grisoni (J. Chem. Inf. Model., 2016)

Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project. - Francesca Grisoni; Viviana Consonni; Davide Ballabio (J. Chem. Inf. Model., 2019)

Bidirectional Molecule Generation with Recurrent Neural Networks. - Francesca Grisoni; Michael Moret; Robin Lingwood; Gisbert Schneider (J. Chem. Inf. Model., 2020)

Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study. - Cecile Valsecchi; Francesca Grisoni; Viviana Consonni; Davide Ballabio (J. Chem. Inf. Model., 2020)

Drug discovery with explainable artificial intelligence. - José Jiménez-Luna; Francesca Grisoni; Gisbert Schneider (Nat. Mach. Intell., 2020)

Generative molecular design in low data regimes. - Michael Moret; Lukas Friedrich; Francesca Grisoni; Daniel Merk; Gisbert Schneider (Nat. Mach. Intell., 2020)

Geometric deep learning on molecular representations. - Kenneth Atz; Francesca Grisoni; Gisbert Schneider (Nat. Mach. Intell., 2021)

Structure-based drug discovery with deep learning. - Riza Özçelik; Derek van Tilborg; José Jiménez-Luna; Francesca Grisoni (CoRR, 2022)

Perplexity-Based Molecule Ranking and Bias Estimation of Chemical Language Models. - Michael Moret; Francesca Grisoni; Paul Katzberger; Gisbert Schneider (J. Chem. Inf. Model., 2022)

Exposing the Limitations of Molecular Machine Learning with Activity Cliffs. - Derek van Tilborg; Alisa Alenicheva; Francesca Grisoni (J. Chem. Inf. Model., 2022)

Correction to "Exposing the Limitations of Molecular Machine Learning with Activity Cliffs". - Derek van Tilborg; Alisa Alenicheva; Francesca Grisoni (J. Chem. Inf. Model., 2023)

Practical guidelines for the use of gradient boosting for molecular property prediction. - Davide Boldini; Francesca Grisoni; Daniel Kuhn; Lukas Friedrich; Stephan A. Sieber (J. Cheminformatics, 2023)

Predicting Metabolic Reactions with a Molecular Transformer for Drug Design Optimization. - Silvia Multari; Riza Özçelik; Angelica Mazzolari; Marco Salvatore Nobile; Francesca Grisoni (CIBCB, 2024)

Integrating genetic algorithms and language models for enhanced enzyme design. - Yves Gaetan Nana Teukam; Federico Zipoli; Teodoro Laino; Emanuele Criscuolo; Francesca Grisoni; Matteo Manica (Briefings Bioinform., 2024)

A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction. - Riza Özçelik; Francesca Grisoni (CoRR, 2024)

Traversing chemical space with active deep learning for low-data drug discovery. - Derek van Tilborg; Francesca Grisoni (Nat. Comput. Sci., 2024)

Effectiveness of molecular fingerprints for exploring the chemical space of natural products. - Davide Boldini; Davide Ballabio; Viviana Consonni; Roberto Todeschini; Francesca Grisoni; Stephan A. Sieber (J. Cheminformatics, 2024)

Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey. - Riza Özçelik; Helena Brinkmann; Emanuele Criscuolo; Francesca Grisoni (J. Chem. Inf. Model., 2025)

Scaffold Hopping with Generative Reinforcement Learning. - Luke Rossen; Finton Sirockin; Nadine Schneider; Francesca Grisoni (J. Chem. Inf. Model., 2025)

The Jungle of Generative Drug Discovery: Traps, Treasures, and Ways Out. - Riza Özçelik; Francesca Grisoni (CoRR, 2025)

Look the Other Way: Designing 'Positive' Molecules with Negative Data via Task Arithmetic. - Riza Özçelik; Sarah de Ruiter; Francesca Grisoni (CoRR, 2025)