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1.
Allesøe, R.L.* et al.: Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models. Nat. Biotechnol. 41, 399-408 (2023)
2.
Allesøe, R.L.* et al.: Author Correction: Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models. Nat. Biotechnol. 41:1026 (2023)
3.
Ertürk, A. & Elsner, M.: Breaking boundaries in whole-body imaging and disease understanding with wildDISCO. Nat. Biotechnol., DOI: 10.1038/s41587-023-01864-y (2023)
4.
Gottschlich, A.* et al.: Single-cell transcriptomic atlas-guided development of CAR-T cells for the treatment of acute myeloid leukemia. Nat. Biotechnol. 41, 1618-1632 (2023)
5.
Kim, D.-K. et al.: A proteome-scale map of the SARS-CoV-2-human contactome. Nat. Biotechnol. 41, 140–149 (2023)
6.
Mai, H. et al.: Whole-body cellular mapping in mouse using standard IgG antibodies. Nat. Biotechnol., DOI: 10.1038/s41587-023-01846-0 (2023)
7.
Meier, A.B.* et al.: Epicardioid single-cell genomics uncovers principles of human epicardium biology in heart development and disease. Nat. Biotechnol. 41, 1787-1800 (2023)
8.
Sigmund, F. et al.: Genetically encoded barcodes for correlative volume electron microscopy. Nat. Biotechnol. 41, 1734–1745 (2023)
9.
Virshup, I. et al.: The scverse project provides a computational ecosystem for single-cell omics data analysis. Nat. Biotechnol. 41, 604-606 (2023)
10.
Fischer, D.S. ; Schaar, A. & Theis, F.J.: Modeling intercellular communication in tissues using spatial graphs of cells. Nat. Biotechnol., DOI: 10.1038/s41587-022-01467-z (2022)
11.
Gaurav, K.* et al.: Population genomic analysis of Aegilops tauschii identifies targets for bread wheat improvement. Nat. Biotechnol. 40, 422–431 (2022)
12.
Gayoso, A.* et al.: A Python library for probabilistic analysis of single-cell omics data. Nat. Biotechnol. 40, 163-166 (2022)
13.
Palla, G. ; Fischer, D.S. ; Regev, A.* & Theis, F.J.: Spatial components of molecular tissue biology. Nat. Biotechnol. 40, 308–318 (2022)
14.
Ringeling, F.R.* et al.: Partitioning RNAs by length improves transcriptome reconstruction from short-read RNA-seq data. Nat. Biotechnol. 40, 741–750 (2022)
15.
Annabi, N.* et al.: Voices of biotech research. Nat. Biotechnol. 39, 281-286 (2021)
16.
Hoffmann, M.A.* et al.: High-confidence structural annotation of metabolites absent from spectral libraries. Nat. Biotechnol. 40, 411–421 (2021)
17.
Lotfollahi, M. et al.: Mapping single-cell data to reference atlases by transfer learning. Nat. Biotechnol., DOI: 10.1038/s41587-021-01001-7 (2021)
18.
Mishra, K. et al.: Genetically encoded photo-switchable molecular sensors for optoacoustic and super-resolution imaging. Nat. Biotechnol., DOI: 10.1038/s41587-021-01100-5 (2021)
19.
Bergen, V. ; Lange, M. ; Peidli, S.* ; Wolf, F.A. & Theis, F.J.: Generalizing RNA velocity to transient cell states through dynamical modeling. Nat. Biotechnol. 38, 1408–1414 (2020)
20.
Mahaddalkar, P.U. et al.: Generation of pancreatic β cells from CD177+ anterior definitive endoderm. Nat. Biotechnol. 38, 1061–1072 (2020)
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