PuSH - Publication Server of Helmholtz Zentrum München

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161.
Kondofersky, I. ; Fuchs, C. & Theis, F.J.: Identifying latent dynamic components in biological systems. IET Syst. Biol. 9, 193-203 (2015)
162.
Kong, B.* et al.: Metabolism gene signatures and surgical site infections in abdominal surgery. Int. J. Surg. 14, 67-74 (2015)
163.
Krumsiek, J. et al.: Gender-specific pathway differences in the human serum metabolome. Metabolomics 11, 1815-1833 (2015)
164.
Linnemann, J. et al.: Quantification of regenerative potential in primary human mammary epithelial cells. Development 142, 3239-3251 (2015)
165.
Loos, C. ; Marr, C. ; Theis, F.J. & Hasenauer, J.: Approximate bayesian computation for stochastic single-cell time-lapse data using multivariate test statistics. Lecture Notes Comp. Sci. 9308, 52-63 (2015)
166.
Marr, C. ; Hasenauer, J. & Theis, F.J.: Models and methods for systems biology and systems medicine: The Institute of Computational Biology at the Helmholtz Zentrum München. Systembiologie.de 9, 40-43 (2015)
167.
Masserdotti, G. et al.: Transcriptional mechanisms of proneural factors and REST in regulating neuronal reprogramming of astrocytes. Cell Stem Cell 17, 74-88 (2015)
168.
Meyer, S.U.* et al.: Integrative analysis of MicroRNA and mRNA data reveals an orchestrated function of MicroRNAs in skeletal myocyte differentiation in response to TNF-α or IGF1. PLoS ONE 10:e0135284 (2015)
169.
Moignard, V.* et al.: Decoding the regulatory network of early blood development from single-cell gene expression measurements. Nat. Biotechnol. 33, 269-276 (2015)
170.
Müller, S.* et al.: Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer. Mol. Cancer 14:94 (2015)
171.
Müller, S.* et al.: Erratum to: Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer. Mol. Cancer 14:144 (2015)
172.
Ocone, A. ; Haghverdi, L. ; Müller, N.S. & Theis, F.J.: Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data. Bioinformatics 31, i89-i96 (2015)
173.
Preusse, M. et al.: SimiRa: A tool to identify coregulation between microRNAs and RNA-binding proteins. RNA Biol. 12, 998-1009 (2015)
174.
Raue, A.* et al.: Data2Dynamics: A modeling environment tailored to parameter estimation in dynamical systems. Bioinformatics 31, 3558-3560 (2015)
175.
Sadic, D.* et al.: Atrx promotes heterochromatin formation at retrotransposons. EMBO Rep. 16, 836-850 (2015)
176.
Sass, S. ; Buettner, F. ; Müller, N.S. & Theis, F.J.: RAMONA: A web application for gene set analysis on multilevel omics data. Bioinformatics 31, 128-130 (2015)
177.
Sass, S. et al.: MicroRNA-target network inference and local network enrichment analysis identify two microRNA clusters with distinct functions in head and neck squamous cell carcinoma. Int. J. Mol. Sci. 16, 30204-30222 (2015)
178.
Schmidt, J. et al.: Stem-cell-like properties and epithelial plasticity arise as stable traits after transient Twist1 activation. Cell Rep. 10, 131-139 (2015)
179.
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)
180.
Theis, F.J. ; Ugelvig, L.V.* ; Marr, C. & Cremer, S.*: Opposing effects of allogrooming on disease transmission in ant societies. Philos. Trans. R. Soc. B - Biol. Sci. 370, DOI: 10.1098/rstb.2014.0108 (2015)