| Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings M Le, S Roller, L Papaxanthos, D Kiela, M Nickel arXiv preprint arXiv:1902.00913, 2019 | 88 | 2019 |
| Proximal optimal transport modeling of population dynamics C Bunne, L Papaxanthos, A Krause, M Cuturi International Conference on Artificial Intelligence and Statistics, 6511-6528, 2022 | 87 | 2022 |
| Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein M Cuturi, L Meng-Papaxanthos, Y Tian, C Bunne, G Davis, O Teboul arXiv preprint arXiv:2201.12324, 2022 | 84 | 2022 |
| Fast and memory-efficient significant pattern mining via permutation testing F Llinares-López, M Sugiyama, L Papaxanthos, K Borgwardt Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 82 | 2015 |
| Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping S Höllerer, L Papaxanthos, AC Gumpinger, K Fischer, C Beisel, ... Nature communications 11 (1), 3551, 2020 | 60 | 2020 |
| Finding significant combinations of features in the presence of categorical covariates L Papaxanthos, F Llinares-López, D Bodenham, K Borgwardt Advances in neural information processing systems 29, 2016 | 39 | 2016 |
| Mapping cells through time and space with moscot D Klein, G Palla, M Lange, M Klein, Z Piran, M Gander, ... bioRxiv, 2023.05. 11.540374, 2023 | 37 | 2023 |
| Machine learning for single-cell genomics data analysis F Raimundo, L Meng-Papaxanthos, C Vallot, JP Vert Current Opinion in Systems Biology 26, 64-71, 2021 | 33 | 2021 |
| Conditional generative modeling for de novo protein design with hierarchical functions T Kucera, M Togninalli, L Meng-Papaxanthos Bioinformatics 38 (13), 3454-3461, 2022 | 29 | 2022 |
| Genome-wide genetic heterogeneity discovery with categorical covariates F Llinares-López, L Papaxanthos, D Bodenham, D Roqueiro, ... Bioinformatics 33 (12), 1820-1828, 2017 | 24 | 2017 |
| Protnlm: Model-based natural language protein annotation A Gane, ML Bileschi, D Dohan, E Speretta, A Héliou, ... Preprint, 2022 | 20 | 2022 |
| Semi-supervised single-cell cross-modality translation using Polarbear R Zhang, L Meng-Papaxanthos, JP Vert, WS Noble International Conference on Research in Computational Molecular Biology, 20-35, 2022 | 18 | 2022 |
| CASMAP: detection of statistically significant combinations of SNPs in association mapping F Llinares-López, L Papaxanthos, D Roqueiro, D Bodenham, K Borgwardt Bioinformatics 35 (15), 2680-2682, 2019 | 14 | 2019 |
| InterPro: the protein sequence classification resource in 2025<? mode longmeta?> M Blum, A Andreeva, LC Florentino, SR Chuguransky, T Grego, E Hobbs, ... Nucleic Acids Research 53 (D1), D444-D456, 2025 | 11 | 2025 |
| The Pfam protein families database: embracing AI/ML T Paysan-Lafosse, A Andreeva, M Blum, SR Chuguransky, T Grego, ... Nucleic Acids Research, gkae997, 2024 | 9 | 2024 |
| ProtNLM: Model-based Natural Language Protein Annotation(2022) A Gane, ML Bileschi, D Dohan, E Speretta, A Héliou, ... | 6 | |
| Multimodal Single-Cell Translation and Alignment with Semi-Supervised Learning R Zhang, L Meng-Papaxanthos, J Vert, WS Noble Journal of Computational Biology 29 (11), 1198-1212, 2022 | 5 | 2022 |
| networkGWAS: a network-based approach to discover genetic associations G Muzio, L O’Bray, L Meng-Papaxanthos, J Klatt, K Fischer, K Borgwardt Bioinformatics 39 (6), btad370, 2023 | 4 | 2023 |
| LSMMD-MA: scaling multimodal data integration for single-cell genomics data analysis L Meng-Papaxanthos, R Zhang, G Li, M Cuturi, WS Noble, JP Vert Bioinformatics 39 (7), btad420, 2023 | 2 | 2023 |
| Deep learning uncovers sequence-specific amplification bias in multi-template PCR AL Gimpel, B Fan, D Chen, LOD Wolfle, M Horn, L Meng-Papaxanthos, ... bioRxiv, 2024.09. 20.614030, 2024 | | 2024 |
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryAdresse e-mail validée de biochem.mpg.de