| An integrated cell atlas of the lung in health and disease L Sikkema, C Ramírez-Suástegui, DC Strobl, TE Gillett, L Zappia, ... Nature medicine 29 (6), 1563-1577, 2023 | 356 | 2023 |
| 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 | 143 | 2023 |
| Machine learning for perturbational single-cell omics Y Ji, M Lotfollahi, FA Wolf, FJ Theis Cell Systems 12 (6), 522-537, 2021 | 104 | 2021 |
| Compositional perturbation autoencoder for single-cell response modeling M Lotfollahi, AK Susmelj, C De Donno, Y Ji, IL Ibarra, FA Wolf, ... BioRxiv, 2021 | 26 | 2021 |
| Machine learning for perturbational single-cell omics. Cell Syst. 12, 522–537 Y Ji, M Lotfollahi, FA Wolf, FJ Theis | 10 | 2021 |
| Pertpy: an end-to-end framework for perturbation analysis L Heumos, Y Ji, L May, T Green, X Zhang, X Wu, J Ostner, S Peidli, ... bioRxiv, 2024.08. 04.606516, 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 | |
| Optimal distance metrics for single-cell RNA-seq populations Y Ji, TD Green, S Peidli, M Bahrami, M Liu, L Zappia, K Hrovatin, ... bioRxiv, 2023.12. 26.572833, 2023 | 3 | 2023 |
| Scalable and universal prediction of cellular phenotypes Y Ji, A Tejada-Lapuerta, NA Schmacke, Z Zheng, X Zhang, S Khan, ... bioRxiv, 2024.08. 12.607533, 2024 | 2 | 2024 |
| Methods and compositions for modulating goblet cells and for muco-obstructive diseases MH Stewart, A Chalkiadaki, JI Yuge, FA Wolf, NMC Plugis, P Hosseini, ... US Patent App. 18/687,654, 2024 | | 2024 |
