| Learning to design RNA F Runge, D Stoll, S Falkner, F Hutter arXiv preprint arXiv:1812.11951, 2018 | 96 | 2018 |
| Probabilistic transformer: Modelling ambiguities and distributions for rna folding and molecule design J Franke, F Runge, F Hutter Advances in Neural Information Processing Systems 35, 26856-26873, 2022 | 14 | 2022 |
| Scalable deep learning for RNA secondary structure prediction JKH Franke, F Runge, F Hutter arXiv preprint arXiv:2307.10073, 2023 | 10 | 2023 |
| RNAformer: A Simple Yet Effective Deep Learning Model for RNA Secondary Structure Prediction JKH Franke, F Runge, R Koeksal, R Backofen, F Hutter bioRxiv, 2024.02. 12.579881, 2024 | 7 | 2024 |
| Partial RNA design F Runge, J Franke, D Fertmann, R Backofen, F Hutter Bioinformatics 40 (Supplement_1), i437-i445, 2024 | 6 | 2024 |
| RnaBench: A Comprehensive Library for In Silico RNA Modelling F Runge, K Farid, JKH Franke, F Hutter bioRxiv, 2024.01. 09.574794, 2024 | 6 | 2024 |
| Rethinking performance measures of rna secondary structure problems F Runge, JKH Franke, D Fertmann, F Hutter arXiv preprint arXiv:2401.05351, 2023 | 2 | 2023 |
| Machine learning for RNA design: Learna F Runge, F Hutter RNA Design: Methods and Protocols, 63-93, 2024 | 1 | 2024 |
| Towards Generative RNA Design With Tertiary Interactions S Patil, F Runge, JKH Franke, F Hutter bioRxiv, 2024.03. 09.584209, 2024 | 1 | 2024 |
| Towards Automated Design of Riboswitches F Runge, JKH Franke, F Hutter arXiv preprint arXiv:2307.08801, 2023 | 1 | 2023 |
| KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks D Scheuer, F Runge, JKH Franke, MT Wolfinger, C Flamm, F Hutter bioRxiv, 2024.10. 15.618378, 2024 | | 2024 |
| RNA-Protein Interaction Classification via Sequence Embeddings D Matus, F Runge, JKH Franke, L Gerne, M Uhl, R Backofen, F Hutter bioRxiv, 2024.11. 08.622607, 2024 | | 2024 |
| Method and device for ascertaining an rna sequence R Backofen, F Hutter, F Runge US Patent App. 17/354,992, 2022 | | 2022 |
| RNA-Protein Interaction Prediction via Sequence Embeddings D Matus, F Runge, JKH Franke, L Gerne, M Uhl, F Hutter, R Backofen, ... | | |
