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1.
Argelaguet, R.* et al.: Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets. Mol. Syst. Biol. 14:e8124 (2018)
2.
Griffiths, J.A.* ; Scialdone, A. & Marioni, J.C.*: Using single-cell genomics to understand developmental processes and cell fate decisions. Mol. Syst. Biol. 14:e8046 (2018)
3.
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)
4.
Tzelepis, K.* et al.: SRPK1 maintains acute myeloid leukemia through effects on isoform usage of epigenetic regulators including BRD4. Nat. Commun. 9:5378 (2018)
5.
Buettner, F. ; Pratanwanich, N.* ; McCarthy, D.J.* ; Marioni, J.C.* & Stegle, O.*: f-scLVM: Scalable and versatile factor analysis for single-cell RNA-seq. Genome Biol. 18:212 (2017)
6.
Regev, A.* et al.: The Human Cell Atlas. eLife 6:e27041 (2017)
7.
Shahbazi, M.N.* et al.: Pluripotent state transitions coordinate morphogenesis in mouse and human embryos. Nature 552, 239-243 (2017)
8.
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)
9.
Scialdone, A.* et al.: Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods 85, 54-61 (2015)