Exposing the Limitations of Molecular Machine Learning with Activity Cliffs D van Tilborg, A Alenicheva, F Grisoni Journal of Chemical Information and Modeling 62 (23), 5938-5951, 2022 | 91 | 2022 |
Structure‐based Drug discovery with Deep Learning R Özçelik, D van Tilborg, J Jiménez-Luna, F Grisoni ChemBioChem, e202200776, 2023 | 24 | 2023 |
PANDORA: a fast, anchor-restrained modelling protocol for peptide: MHC complexes DF Marzella, FM Parizi, D Tilborg, N Renaud, D Sybrandi, R Buzatu, ... Frontiers in Immunology 13, 878762, 2022 | 19* | 2022 |
Deep learning for low-data drug discovery: hurdles and opportunities D van Tilborg, H Brinkmann, E Criscuolo, L Rossen, R Özçelik, F Grisoni Current Opinion in Structural Biology 86, 102818, 2024 | 6 | 2024 |
Cancers in Agreement? Exploring the Cross-Talk of Cancer Metabolomic and Transcriptomic Landscapes Using Publicly Available Data D van Tilborg, E Saccenti Cancers 13 (3), 393, 2021 | 3 | 2021 |
Machine learning-guided high throughput nanoparticle design A Ortiz-Perez, D van Tilborg, R van der Meel, F Grisoni, L Albertazzi Digital Discovery, 2024 | 2 | 2024 |
Traversing Chemical Space with Active Deep Learning D van Tilborg, F Grisoni | 2 | 2023 |
Traversing Chemical Space with Active Deep Learning: A Computational Framework for Low-data Drug Discovery D van Tilborg, F Grisoni | | 2024 |
Computational models of synergy contribute to efficient combination screening JCM Uitdehaag, MBW Prinsen, DW van Tilborg, JJ Kooijman, J Dylus, ... Sigma 2, 0, 2019 | | 2019 |
Combining cell panel profiling and synthetic lethality data to efficiently screen for synergistic combinations JC Uitdehaag, DW Tilborg, MBW Prinsen, JJ Kooijman, J Dylus, ... Cancer Research 79 (13_Supplement), 2158-2158, 2019 | | 2019 |