Teichmann SA - Search Results

1

Single-cell transcriptomics identifies CD44 as a marker and regulator of endothelial to haematopoietic transition.

Oatley M, Bölükbası ÖV, Svensson V, Shvartsman M, Ganter K, Zirngibl K, Pavlovich PV, Milchevskaya V, Foteva V, Natarajan KN, Baying B, Benes V, Patil KR, Teichmann SA, Lancrin C. Oatley M, et al. Among authors: teichmann sa. Nat Commun. 2020 Jan 29;11(1):586. doi: 10.1038/s41467-019-14171-5. Nat Commun. 2020. PMID: 31996681 Free PMC article.

2

Accounting for technical noise in single-cell RNA-seq experiments.

Brennecke P, Anders S, Kim JK, Kołodziejczyk AA, Zhang X, Proserpio V, Baying B, Benes V, Teichmann SA, Marioni JC, Heisler MG. Brennecke P, et al. Among authors: teichmann sa. Nat Methods. 2013 Nov;10(11):1093-5. doi: 10.1038/nmeth.2645. Epub 2013 Sep 22. Nat Methods. 2013. PMID: 24056876

3

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.

Buettner F, Natarajan KN, Casale FP, Proserpio V, Scialdone A, Theis FJ, Teichmann SA, Marioni JC, Stegle O. Buettner F, et al. Among authors: teichmann sa. Nat Biotechnol. 2015 Feb;33(2):155-60. doi: 10.1038/nbt.3102. Epub 2015 Jan 19. Nat Biotechnol. 2015. PMID: 25599176

4

Computational and analytical challenges in single-cell transcriptomics.

Stegle O, Teichmann SA, Marioni JC. Stegle O, et al. Among authors: teichmann sa. Nat Rev Genet. 2015 Mar;16(3):133-45. doi: 10.1038/nrg3833. Epub 2015 Jan 28. Nat Rev Genet. 2015. PMID: 25628217 Review.

5

An atlas of mouse CD4(+) T cell transcriptomes.

Stubbington MJ, Mahata B, Svensson V, Deonarine A, Nissen JK, Betz AG, Teichmann SA. Stubbington MJ, et al. Among authors: teichmann sa. Biol Direct. 2015 Apr 3;10:14. doi: 10.1186/s13062-015-0045-x. Biol Direct. 2015. PMID: 25886751 Free PMC article.

6

The technology and biology of single-cell RNA sequencing.

Kolodziejczyk AA, Kim JK, Svensson V, Marioni JC, Teichmann SA. Kolodziejczyk AA, et al. Among authors: teichmann sa. Mol Cell. 2015 May 21;58(4):610-20. doi: 10.1016/j.molcel.2015.04.005. Mol Cell. 2015. PMID: 26000846 Free article. Review.

7

Computational assignment of cell-cycle stage from single-cell transcriptome data.

Scialdone A, Natarajan KN, Saraiva LR, Proserpio V, Teichmann SA, Stegle O, Marioni JC, Buettner F. Scialdone A, et al. Among authors: teichmann sa. Methods. 2015 Sep 1;85:54-61. doi: 10.1016/j.ymeth.2015.06.021. Epub 2015 Jul 2. Methods. 2015. PMID: 26142758 Free article.

8

Single Cell RNA-Sequencing of Pluripotent States Unlocks Modular Transcriptional Variation.

Kolodziejczyk AA, Kim JK, Tsang JC, Ilicic T, Henriksson J, Natarajan KN, Tuck AC, Gao X, Bühler M, Liu P, Marioni JC, Teichmann SA. Kolodziejczyk AA, et al. Among authors: teichmann sa. Cell Stem Cell. 2015 Oct 1;17(4):471-85. doi: 10.1016/j.stem.2015.09.011. Cell Stem Cell. 2015. PMID: 26431182 Free PMC article.

9

Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression.

Kim JK, Kolodziejczyk AA, Ilicic T, Teichmann SA, Marioni JC. Kim JK, et al. Among authors: teichmann sa. Nat Commun. 2015 Oct 22;6:8687. doi: 10.1038/ncomms9687. Nat Commun. 2015. PMID: 26489834 Free PMC article.

10

Single-Cell RNA-Sequencing Reveals a Continuous Spectrum of Differentiation in Hematopoietic Cells.

Macaulay IC, Svensson V, Labalette C, Ferreira L, Hamey F, Voet T, Teichmann SA, Cvejic A. Macaulay IC, et al. Among authors: teichmann sa. Cell Rep. 2016 Feb 2;14(4):966-977. doi: 10.1016/j.celrep.2015.12.082. Epub 2016 Jan 21. Cell Rep. 2016. PMID: 26804912 Free PMC article.

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