| SignalP 5.0 improves signal peptide predictions using deep neural networks JJ Almagro Armenteros, KD Tsirigos, CK Sønderby, TN Petersen, ... Nature biotechnology 37 (4), 420-423, 2019 | 3953 | 2019 |
| DeepLoc: prediction of protein subcellular localization using deep learning JJ Almagro Armenteros, CK Sønderby, SK Sønderby, H Nielsen, ... Bioinformatics 33 (21), 3387-3395, 2017 | 1127 | 2017 |
| Ladder variational autoencoders CK Sønderby, T Raiko, L Maaløe, SK Sønderby, O Winther Neural Information Processing Systems, 2016 | 1112* | 2016 |
| NetSurfP‐2.0: Improved prediction of protein structural features by integrated deep learning MS Klausen, MC Jespersen, H Nielsen, KK Jensen, VI Jurtz, ... Proteins: Structure, Function, and Bioinformatics 87 (6), 520-527, 2019 | 584 | 2019 |
| Auxiliary deep generative models L Maaløe, CK Sønderby, SK Sønderby, O Winther International conference on machine learning, 1445-1453, 2016 | 543 | 2016 |
| Amortised map inference for image super-resolution CK Sønderby, J Caballero, L Theis, W Shi, F Huszár International Conference on Learning Representations (ICLR), 2016 | 536 | 2016 |
| Improved metagenome binning and assembly using deep variational autoencoders JN Nissen, J Johansen, RL Allesøe, CK Sønderby, JJA Armenteros, ... Nature biotechnology 39 (5), 555-560, 2021 | 394 | 2021 |
| Metnet: A neural weather model for precipitation forecasting CK Sønderby, L Espeholt, J Heek, M Dehghani, A Oliver, T Salimans, ... arXiv preprint arXiv:2003.12140, 2020 | 336 | 2020 |
| BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis FO Bagger, D Sasivarevic, SH Sohi, LG Laursen, S Pundhir, CK Sønderby, ... Nucleic acids research 44 (D1), D917-D924, 2016 | 329 | 2016 |
| Orientationally invariant metrics of apparent compartment eccentricity from double pulsed field gradient diffusion experiments SN Jespersen, H Lundell, CK Sønderby, TB Dyrby NMR in Biomedicine 26 (12), 1647-1662, 2013 | 269 | 2013 |
| Deep learning for twelve hour precipitation forecasts L Espeholt, S Agrawal, C Sønderby, M Kumar, J Heek, C Bromberg, ... Nature communications 13 (1), 1-10, 2022 | 225 | 2022 |
| scVAE: variational auto-encoders for single-cell gene expression data CH Grønbech, MF Vording, PN Timshel, CK Sønderby, TH Pers, ... Bioinformatics 36 (16), 4415-4422, 2020 | 223 | 2020 |
| An introduction to deep learning on biological sequence data: examples and solutions VI Jurtz, AR Johansen, M Nielsen, JJ Almagro Armenteros, H Nielsen, ... Bioinformatics 33 (22), 3685-3690, 2017 | 177 | 2017 |
| Convolutional LSTM networks for subcellular localization of proteins SK Sønderby, CK Sønderby, H Nielsen, O Winther Algorithms for Computational Biology: Second International Conference, AlCoB …, 2015 | 168 | 2015 |
| Recurrent spatial transformer networks SK Sønderby, CK Sønderby, L Maaløe, O Winther arXiv preprint arXiv:1509.05329, 2015 | 70 | 2015 |
| Idf++: Analyzing and improving integer discrete flows for lossless compression R Berg, AA Gritsenko, M Dehghani, CK Sønderby, T Salimans arXiv preprint arXiv:2006.12459, 2020 | 51 | 2020 |
| Diffusion weighted imaging with circularly polarized oscillating gradients H Lundell, CK Sønderby, TB Dyrby Magnetic resonance in medicine 73 (3), 1171-1176, 2015 | 46 | 2015 |
| Tumor suppressor ASXL1 is essential for the activation of INK4B expression in response to oncogene activity and anti-proliferative signals X Wu, IH Bekker-Jensen, J Christensen, KD Rasmussen, S Sidoli, Y Qi, ... Cell research 25 (11), 1205-1218, 2015 | 45 | 2015 |
| Apparent exchange rate imaging in anisotropic systems CK Sønderby, HM Lundell, LV Søgaard, TB Dyrby Magnetic resonance in medicine 72 (3), 756-762, 2014 | 40 | 2014 |
| Continuous Relaxation Training of Discrete Latent Variable Image Models CK Sønderby, B Poole, A Mnih Bayesian Deeplearning Workshop, Neurips, 2017 | 27 | 2017 |
Henrik LundellAssoc. Profess MR Section, DTU Health Technology and Danish Research Centre for Magnetic ResonanceVerified email at drcmr.dk
