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1.
Bandi, V.G.* et al.: Targeted multicolor in vivo imaging over 1,000 nm enabled by nonamethine cyanines. Nat. Methods 19, 353–358 (2022)
2.
Giansanti, P.* et al.: Mass spectrometry-based draft of the mouse proteome. Nat. Methods 19, 803-811 (2022)
3.
Lange, M. et al.: CellRank for directed single-cell fate mapping. Nat. Methods 19, 159–170 (2022)
4.
Luecken, M. et al.: Benchmarking atlas-level data integration in single-cell genomics. Nat. Methods 19, 41-50 (2022)
5.
Palla, G. et al.: Squidpy: A scalable framework for spatial omics analysis. Nat. Methods 19, 171–178 (2022)
6.
Matschinske, J.* et al.: The AIMe registry for artificial intelligence in biomedical research. Nat. Methods, DOI: 10.1038/s41592-021-01241-0 (2021)
7.
Moebel, E.* et al.: Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms. Nat. Methods 18, 1386-1394 (2021)
8.
Moebel, E.* et al.: Author Correction: Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms (Nature Methods, (2021), 18, 11, (1386-1394), 10.1038/s41592-021-01275-4). Nat. Methods, DOI: 10.1038/s41592-021-01349-3 (2021)
9.
Nothias, L.F.* et al.: Feature-based molecular networking in the GNPS analysis environment. Nat. Methods 17, 905–908 (2020)
10.
Todorov, M.I. et al.: Machine learning analysis of whole mouse brain vasculature. Nat. Methods 17, 442-449 (2020)
11.
Büttner, M. ; Miao, Z.* ; Wolf, F.A. ; Teichmann, S.A.* & Theis, F.J.: A test metric for assessing single-cell RNA-seq batch correction. Nat. Methods 16, 43-49 (2019)
12.
Lotfollahi, M. ; Wolf, F.A. & Theis, F.J.: scGen predicts single-cell perturbation responses. Nat. Methods 16, 715-721 (2019)
13.
Qian, Y.* et al.: A genetically encoded near-infrared fluorescent calcium ion indicator. Nat. Methods 16, 171-174 (2019)
14.
Weigert, M.* et al.: Content-aware image restoration: Pushing the limits of fluorescence microscopy. Nat. Methods 15, 1090-1097 (2018)
15.
Azencott, C.* et al.: The inconvenience of data of convenience: Computational research beyond post-mortem analyses. Nat. Methods 14, 937-938 (2017)
16.
Buggenthin, F. et al.: Prospective identification of hematopoietic lineage choice by deep learning. Nat. Methods, DOI: 10.1038/nmeth.4182 (2017)
17.
Nasr, M.L.* et al.: Covalently circularized nanodiscs for studying membrane proteins and viral entry. Nat. Methods 14, 49-52 (2017)
18.
Symvoulidis, P. et al.: NeuBtracker-imaging neurobehavioral dynamics in freely behaving fish. Nat. Methods 14, 1079-1082 (2017)
19.
Van Deun, J.* et al.: EV-TRACK: Transparent reporting and centralizing knowledge in extracellular vesicle research. Nat. Methods 14, 228-232 (2017)
20.
Haghverdi, L. ; Büttner, M. ; Wolf, F.A. ; Buettner, F. & Theis, F.J.: Diffusion pseudotime robustly reconstructs lineage branching. Nat. Methods 13, 845-848 (2016)