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Bast, L. et al.: Increasing neural stem cell division asymmetry and quiescence are predicted to contribute to the age-related decline in neurogenesis. Cell Rep. 25, 3231-3240.e8 (2018)
Strasser, M. et al.: Lineage marker synchrony in hematopoietic genealogies refutes the PU.1/GATA1 toggle switch paradigm. Nat. Commun. 9:2697 (2018)
Blasi, T. ; Buettner, F. ; Strasser, M. ; Marr, C. & Theis, F.J.: CgCorrect: A method to correct for confounding cell-cell variation due to cell growth in single-cell transcriptomics. Phys. Biol. 14:036001 (2017)
Buggenthin, F. et al.: Prospective identification of hematopoietic lineage choice by deep learning. Nat. Methods, DOI: 10.1038/nmeth.4182 (2017)
Hilsenbeck, O. et al.: Software tools for single-cell tracking and quantification of cellular and molecular properties. Nat. Biotechnol. 34, 703-706 (2016)
Hoppe, P.S. et al.: Early myeloid lineage choice is not initiated by random PU.1 to GATA1 protein ratios. Nature 535, 299-302 (2016)
Mishra, M. et al.: Structure-based assessment of cancerous mitochondria using deep networks. In: Proceedings (Proceedings / IEEE 13th International Symposium on Biomedical Imaging (ISBI), 13-16 April 2016, Prague, Czech Republic). IEEE, 2016.
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)
Strasser, M.: From single cells to genealogies: Stochastic models of stem cell differentiation. München, Technische Universität, Fakultät Wissenschaftszentrum Weihenstephan, Diss., 2015, 150 S.
Marr, C. ; Strasser, M. ; Schwarzfischer, M. ; Schroeder, T. & Theis, F.J.: Multi-scale modeling of GMP differentiation based on single-cell genealogies. FEBS J. 279, 3488-3500 (2012)
Strasser, M. ; Theis, F.J. & Marr, C.: Stability and multiattractor dynamics of a toggle switch based on a two-stage model of stochastic gene expression. Biophys. J. 102, 19-29 (2012)
Strasser, M.: Stochastic modeling in gene switches. München, Ludwig-Maximilians-Universität & Technische Universität, Bioinformatik, Master-Thesis, 2010, 81 S.