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1.
Blasi, T. et al.: Combinatorial histone acetylation patterns are generated by motif-specific reactions. Cell Syst. 2, 49-58 (2016)
2.
Feigelman, J.: Stochastic and deterministic methods for the analysis of Nanog dynamics in mouse embryonic stem cells. München, Technische Universität, Fakultät für Mathematik, Diss., 2016, 194 S.
3.
Feigelman, J. et al.: Analysis of cell lineage trees by exact bayesian inference identifies negative autoregulation of nanog in mouse embryonic stem cells. Cell Syst. 3, 480-490 (2016)
4.
Hilsenbeck, O. et al.: Software tools for single-cell tracking and quantification of cellular and molecular properties. Nat. Biotechnol. 34, 703-706 (2016)
5.
Feigelman, J. ; Popovic, N.* & Marr, C.: A case study on the use of scale separation-based analytical propagators for parameter inference in models of stochastic gene regulation. J. Coupled Syst. Multiscale Dyn. 3, 164-173 (2015)
6.
Filipczyk, A. et al.: Network plasticity of pluripotency transcription factors in embryonic stem cells. Nat. Cell Biol. 17, 1235-1246 (2015)
7.
Strasser, M. ; Feigelman, J. ; Theis, F.J. & Marr, C.: Inference of spatiotemporal effects on cellular state transitions from time-lapse microscopy. BMC Syst. Biol. 9:61 (2015)
8.
Feigelman, J. ; Theis, F.J. & Marr, C.: MCA: Multiresolution Correlation Analysis, a graphical tool for subpopulation identification in single-cell gene expression data. BMC Bioinformatics 15:240 (2014)