| The shapley value in machine learning B Rozemberczki, L Watson, P Bayer, HT Yang, O Kiss, S Nilsson, ... arXiv preprint arXiv:2202.05594, 2022 | 178 | 2022 |
| Chemicalx: A deep learning library for drug pair scoring B Rozemberczki, CT Hoyt, A Gogleva, P Grabowski, K Karis, A Lamov, ... Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 25 | 2022 |
| Biological Insights Knowledge Graph: an integrated knowledge graph to support drug development D Geleta, A Nikolov, G Edwards, A Gogleva, R Jackson, E Jansson, ... Biorxiv, 2021.10. 28.466262, 2021 | 21 | 2021 |
| Moomin: Deep molecular omics network for anti-cancer drug combination therapy B Rozemberczki, A Gogleva, S Nilsson, G Edwards, A Nikolov, E Papa Proceedings of the 31st ACM international conference on information …, 2022 | 18 | 2022 |
| A unified view of relational deep learning for drug pair scoring B Rozemberczki, S Bonner, A Nikolov, M Ughetto, S Nilsson, E Papa arXiv preprint arXiv:2111.02916, 2021 | 16 | 2021 |
| Explainable biomedical recommendations via reinforcement learning reasoning on knowledge graphs G Edwards, S Nilsson, B Rozemberczki, E Papa arXiv preprint arXiv:2111.10625, 2021 | 11 | 2021 |
| A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction B Rozemberczki, S Bonner, A Nikolov, M Ughetto, S Nilsson, E Papa arXiv e-prints, arXiv: 2111.02916, 2021 | | 2021 |
| Comparison of State-of-the-art Algorithms for de novo Drug Design S Nilsson, J Sundkvist | | 2020 |
