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1.
Hug, S. ; Schmidl, D. ; Li, W.B. ; Greiter, M. & Theis, F.J.: Bayesian model selection methods and their application to biological ODE systems. In: Geris, L.* ; Gomez-Cabrero, D.* [Eds.]: Uncertainty in Biology : A Computational Modeling Approach. Berlin; Heidelberg: Springer, 2016. 243-268 (Stud. Mechanobiol. Tiss. Engineering Biomater. ; 17)
2.
Abend, M.* et al.: Gene expression analysis in Mayak workers with prolonged occupational radiation exposure. Health Phys. 106, 664-676 (2014)
3.
Wilke, C. et al.: Comparative global characterisation of microRNA-expression in radiation-associated and sporadic breast carcinomas. Eur. J. Cancer 50, S229 (2014)
4.
Schmidl, D. ; Czado, C.* ; Hug, S. & Theis, F.J.: A vine-copula based adaptive MCMC sampler for efficient inference of dynamical systems. Bayesian Anal. 8, 1-22 (2013)
5.
Schmidl, D. ; Czado, C.* ; Hug, S. & Theis, F.J.: Rejoinder on "A vine-copula based adaptive MCMC sampler for efficient inference of dynamical systems". Bayesian Anal. 8, 33-42 (2013)
6.
Schmidl, D. ; Hug, S. ; Li, W.B. ; Greiter, M. & Theis, F.J.: Bayesian model selection validates a biokinetic model for zirconium processing in humans. BMC Syst. Biol. 6:95 (2012)
7.
Schmidl, D.: Bayesian model inference in dynamic biological systems using Markov Chain Monte Carlo methods. München, Technische Universität, Fakultät für Mathematik, Diss., 2012, 220 S.
8.
Kowarsch, A. ; Marr, C. ; Schmidl, D. ; Ruepp, A. & Theis, F.J.: Tissue-specific target analysis of disease-associated microRNAs in human signaling pathways. PLoS ONE 5:e11154 (2010)
9.
Ruepp, A. et al.: PhenomiR: A knowledgebase for microRNA expression in diseases and biological processes. Genome Biol. 11:R6 (2010)
10.
Wittmann, D.M. ; Schmidl, D. ; Blöchl, F. & Theis, F.J.: Reconstruction of graphs based on random walks. Theor. Comput. Sci. 410, 3826-3838 (2009)