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ORCIDFrancesca Grisoni
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- affiliation: Eindhoven University of Technology, The Netherlands
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2020 – today
- 2024
[j13]Davide Boldini, Davide Ballabio
, Viviana Consonni, Roberto Todeschini, Francesca Grisoni, Stephan A. Sieber:
Effectiveness of molecular fingerprints for exploring the chemical space of natural products. J. Cheminformatics 16(1): 35 (2024)- [j12]Derek van Tilborg, Francesca Grisoni:
Traversing chemical space with active deep learning for low-data drug discovery. Nat. Comput. Sci. 4(10): 786-796 (2024) - [c1]Silvia Multari, Riza Özçelik, Angelica Mazzolari, Marco Salvatore Nobile, Francesca Grisoni:
Predicting Metabolic Reactions with a Molecular Transformer for Drug Design Optimization. CIBCB 2024: 1-8 - [i4]Riza Özçelik, Francesca Grisoni:
A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction. CoRR abs/2407.12152 (2024) - 2023
- [j11]Davide Boldini, Francesca Grisoni, Daniel Kuhn, Lukas Friedrich, Stephan A. Sieber:
Practical guidelines for the use of gradient boosting for molecular property prediction. J. Cheminformatics 15(1): 73 (2023) - [j10]Derek van Tilborg, Alisa Alenicheva, Francesca Grisoni:
Correction to "Exposing the Limitations of Molecular Machine Learning with Activity Cliffs". J. Chem. Inf. Model. 63(7): 2266 (2023) - 2022
- [j9]Michael Moret, Francesca Grisoni, Paul Katzberger, Gisbert Schneider:
Perplexity-Based Molecule Ranking and Bias Estimation of Chemical Language Models. J. Chem. Inf. Model. 62(5): 1199-1206 (2022) - [j8]Derek van Tilborg, Alisa Alenicheva, Francesca Grisoni:
Exposing the Limitations of Molecular Machine Learning with Activity Cliffs. J. Chem. Inf. Model. 62(23): 5938-5951 (2022) - [i3]Riza Özçelik, Derek van Tilborg, José Jiménez-Luna, Francesca Grisoni:
Structure-based drug discovery with deep learning. CoRR abs/2212.13295 (2022) - 2021
- [j7]Kenneth Atz, Francesca Grisoni, Gisbert Schneider:
Geometric deep learning on molecular representations. Nat. Mach. Intell. 3(12): 1023-1032 (2021) - [i2]Kenneth Atz, Francesca Grisoni, Gisbert Schneider:
Geometric Deep Learning on Molecular Representations. CoRR abs/2107.12375 (2021) - 2020
- [j6]Francesca Grisoni, Michael Moret, Robin Lingwood, Gisbert Schneider:
Bidirectional Molecule Generation with Recurrent Neural Networks. J. Chem. Inf. Model. 60(3): 1175-1183 (2020) - [j5]Cecile Valsecchi, Francesca Grisoni, Viviana Consonni, Davide Ballabio:
Consensus versus Individual QSARs in Classification: Comparison on a Large-Scale Case Study. J. Chem. Inf. Model. 60(3): 1215-1223 (2020) - [j4]Michael Moret, Lukas Friedrich, Francesca Grisoni, Daniel Merk, Gisbert Schneider:
Generative molecular design in low data regimes. Nat. Mach. Intell. 2(3): 171-180 (2020) - [j3]José Jiménez-Luna, Francesca Grisoni, Gisbert Schneider:
Drug discovery with explainable artificial intelligence. Nat. Mach. Intell. 2(10): 573-584 (2020) - [i1]José Jiménez-Luna, Francesca Grisoni, Gisbert Schneider:
Drug discovery with explainable artificial intelligence. CoRR abs/2007.00523 (2020)
2010 – 2019
- 2019
- [j2]Francesca Grisoni, Viviana Consonni, Davide Ballabio:
Machine Learning Consensus To Predict the Binding to the Androgen Receptor within the CoMPARA Project. J. Chem. Inf. Model. 59(5): 1839-1848 (2019) - 2016
- [j1]Roberto Todeschini, Davide Ballabio, Francesca Grisoni:
Beware of Unreliable Q2! A Comparative Study of Regression Metrics for Predictivity Assessment of QSAR Models. J. Chem. Inf. Model. 56(10): 1905-1913 (2016)
Coauthor Index
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