| Predicting cellular responses to complex perturbations in high‐throughput screens M Lotfollahi, A Klimovskaia Susmelj, C De Donno, L Hetzel, Y Ji, IL Ibarra, ... Molecular systems biology 19 (6), e11517, 2023 | 173* | 2023 |
| Poincaré Maps for Analyzing Complex Hierarchies in Single-Cell Data MN A Klimovskaia, D Lopez-Paz, L Bottou Nature Communications 11 (1), 1--9, 2019 | 112* | 2019 |
| Sparse regression based structure learning of stochastic reaction networks from single cell snapshot time series A Klimovskaia, S Ganscha, M Claassen PLoS computational biology 12 (12), e1005234, 2016 | 22 | 2016 |
| Carlo De Donno, Leon Hetzel, Yuge Ji, Ignacio L Ibarra, Sanjay R Srivatsan, Mohsen Naghipourfar, Riza M Daza, Beth Martin, et al. Predicting cellular responses to complex … M Lotfollahi, AK Susmelj Molecular Systems Biology, page e11517, 2023 | 19 | 2023 |
| Carlo De Donno M Lotfollahi, AK Susmelj Yuge Ji, Ignacio L Ibarra, F Alexander Wolf, Nafissa Yakubova, Fabian J …, 2021 | 17 | 2021 |
| Comprehensive characterization of ureagenesis in the spfash mouse, a model of human ornithine transcarbamylase deficiency, reveals age‐dependency of … G Allegri, S Deplazes, N Rimann, B Causton, T Scherer, JW Leff, ... Journal of inherited metabolic disease 42 (6), 1064-1076, 2019 | 14 | 2019 |
| An upper bound for random measurement error in causal discovery T Blom, A Klimovskaia, S Magliacane, JM Mooij arXiv preprint arXiv:1810.07973, 2018 | 14 | 2018 |
| Signal domain learning approach for optoacoustic image reconstruction from limited view data AK Susmelj, B Lafci, F Ozdemir, N Davoudi, XL Dean-Ben, F Perez-Cruz, ... International Conference on Medical Imaging with Deep Learning, 1173-1191, 2022 | 6* | 2022 |
| Signal domain adaptation network for limited-view optoacoustic tomography AK Susmelj, B Lafci, F Ozdemir, N Davoudi, XL Deán-Ben, F Perez-Cruz, ... Medical Image Analysis 91, 103012, 2024 | 5 | 2024 |
| Learning Interpretable Cellular Responses to Complex Perturbations in High-Throughput Screens. BioRxiv 2021 M Lotfollahi, AK Susmelj, C De Donno, Y Ji, IL Ibarra, FA Wolf, ... https://www. biorxiv. org/content/10.110 1 (2021.04), 14.439903, 0 | 4 | |
| Poincaré maps for visualization of large protein families AK Susmelj, Y Ren, Y Vander Meersche, JC Gelly, T Galochkina Briefings in Bioinformatics 24 (3), bbad103, 2023 | 3 | 2023 |
| Uncertainty modeling for fine-tuned implicit functions A Susmelj, M Macuglia, N Tagasovska, R Sutter, S Caprara, JP Thiran, ... arXiv preprint arXiv:2406.12082, 2024 | 2 | 2024 |
| Pseudo-Euclidean Attract-Repel Embeddings for Undirected Graphs A Peysakhovich, AK Susmel, L Bottou arXiv preprint arXiv:2106.09671, 2021 | 1 | 2021 |
| Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal Mechanisms B Chen, Y Zhu, Y Ao, S Caprara, R Sutter, G Rätsch, E Konukoglu, ... arXiv preprint arXiv:2411.05223, 2024 | | 2024 |
| Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation? K Cekmeceli, M Himmetoglu, GI Tombak, A Susmelj, E Erdil, E Konukoglu arXiv preprint arXiv:2409.07960, 2024 | | 2024 |
| Proceedings of the EuBIC-MS developers meeting 2023 Journal of Proteomics, 2024 | | 2024 |
| Identification of causal mechanisms of cell variability in signaling networks from single-cell time series snapshots A Klimovskaia ETH Zurich, 2019 | | 2019 |
David Lopez-PazFAIR at MetaVerified email at fb.com