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Gaurav, K.* et al.: Population genomic analysis of Aegilops tauschii identifies targets for bread wheat improvement. Nat. Biotechnol. 40, 422–431 (2022)
Gayoso, A.* et al.: A Python library for probabilistic analysis of single-cell omics data. Nat. Biotechnol. 40, 163-166 (2022)
Palla, G. ; Fischer, D.S. ; Regev, A.* & Theis, F.J.: Spatial components of molecular tissue biology. Nat. Biotechnol. 40, 308–318 (2022)
Ringeling, F.R.* et al.: Partitioning RNAs by length improves transcriptome reconstruction from short-read RNA-seq data. Nat. Biotechnol. 40, 741–750 (2022)
Annabi, N.* et al.: Voices of biotech research. Nat. Biotechnol. 39, 281-286 (2021)
Hoffmann, M.A.* et al.: High-confidence structural annotation of metabolites absent from spectral libraries. Nat. Biotechnol. 40, 411–421 (2021)
Lotfollahi, M. et al.: Mapping single-cell data to reference atlases by transfer learning. Nat. Biotechnol., DOI: 10.1038/s41587-021-01001-7 (2021)
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)
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)
Mahaddalkar, P.U. et al.: Generation of pancreatic β cells from CD177+ anterior definitive endoderm. Nat. Biotechnol. 38, 1061–1072 (2020)
Pleitez, M.A. et al.: Label-free metabolic imaging by mid-infrared optoacoustic microscopy in living cells. Nat. Biotechnol. 38, 293-296 (2020)
Fischer, D.S. et al.: Inferring population dynamics from single-cell RNA-sequencing time series data. Nat. Biotechnol. 37, 461-468 (2019)
Haghverdi, L. ; Lun, A.T.L.* ; Morgan, M.D.* & Marioni, J.C.*: Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors. Nat. Biotechnol. 36, 421-427 (2018)
Hilsenbeck, O. et al.: Software tools for single-cell tracking and quantification of cellular and molecular properties. Nat. Biotechnol. 34, 703-706 (2016)
Buettner, F. et al.: Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. Biotechnol. 33, 155-160 (2015)
Chu, V.T.* et al.: Increasing the efficiency of homology-directed repair for CRISPR-Cas9-induced precise gene editing in mammalian cells. Nat. Biotechnol. 33, 543-548 (2015)
Küffner, R. et al.: Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression. Nat. Biotechnol. 33, 51-57 (2015)
Moignard, V.* et al.: Decoding the regulatory network of early blood development from single-cell gene expression measurements. Nat. Biotechnol. 33, 269-276 (2015)
Drukker, M. et al.: Isolation of primitive endoderm, mesoderm, vascular endothelial and trophoblast progenitors from human pluripotent stem cells. Nat. Biotechnol. 30, 531-542 (2012)
Wichmann, H.-E. et al.: Comprehensive catalog of European biobanks. Nat. Biotechnol. 29, 795-797 (2011)