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181.
Wahl, S. et al.: Multi-omic signature of body weight change: Results from a population-based cohort study. BMC Med. 13:48 (2015)
182.
Wang, L. et al.: Anatomic-landmark detection using graphical context modelling. In: Proceedings (12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, 16-19 April 2015, Brooklyn, United States). 2015. 1304-1307
183.
Wilson, N.K.* et al.: Combined single-cell functional and gene expression analysis resolves heterogeneity within stem cell populations. Cell Stem Cell 16, 712-724 (2015)
184.
Albrecht, E. et al.: Metabolite profiling reveals new insights into the regulation of serum urate in humans. Metabolomics 10, 141-151 (2014)
185.
Bajikar, S.S.* ; Fuchs, C. ; Roller, A. ; Theis, F.J. & Janes, K.A.*: Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles. Proc. Natl. Acad. Sci. U.S.A. 111, E626-E635 (2014)
186.
Bartel, S. et al.: MicroRNA-based identification of epithelial SEC14L3 loss in experimental and human paediatric asthma. Allergy 69, 40-41 (2014)
187.
Baumann, S.* et al.: Subtoxic concentrations of benzo[a]pyrene induce metabolic changes and oxidative stress in non-activated and affect the mTOR pathway in activated Jurkat T cells. J. Integr. OMICS, DOI: 10.5584/jiomics.v4i1.157 (2014)
188.
Bonifacio, E.* ; Krumsiek, J. ; Winkler, C. ; Theis, F.J. & Ziegler, A.-G.: A strategy to find gene combinations that identify children who progress rapidly to type 1 diabetes after islet autoantibody seroconversion. Acta Diabetol. 51, 403-411 (2014)
189.
Buettner, F. ; Moignard, V.* ; Göttgens, B.* & Theis, F.J.: Probabilistic PCA of censored data: Accounting for uncertainties in the visualisation of high-throughput single-cell qPCR data. Bioinformatics 30, 1867-1875 (2014)
190.
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)
191.
Fröhlich, F. ; Theis, F.J. & Hasenauer, J.: Uncertainty analysis for non-identifiable dynamical systems: Profile likelihoods, bootstrapping and more. Lecture Notes Comp. Sci. 8859, 61-72 (2014)
192.
Fröhlich, F. ; Hross, S. ; Theis, F.J. & Hasenauer, J.: Radial basis function approximations of Bayesian parameter posterior densities for uncertainty analysis. Lecture Notes Comp. Sci. 8859, 73-85 (2014)
193.
Garzorz, N.V.* et al.: Intra-individual genome expression analysis reveals a specific molecular signature of psoriasis and eczema. J. Invest. Dermatol. 134, S1 (2014)
194.
Garzorz-Stark, N.* et al.: Eczema ≠ eczema: The transcriptional heterogeneity of eczema. Br. J. Dermatol. 170, E19 (2014)
195.
Hasenauer, J. ; Wolf, V.* ; Kazeroonian, A. & Theis, F.J.: Method of conditional moments (MCM) for the chemical master equation: A unified framework for the method of moments and hybrid stochastic-deterministic models. J. Math. Biol. 69, 687-735 (2014)
196.
Hasenauer, J. ; Hasenauer, C.* ; Hucho, T.* & Theis, F.J.: ODE constrained mixture modelling: A method for unraveling subpopulation structures and dynamics. PLoS Comput. Biol. 10:e1003686 (2014)
197.
Illner, K. ; Fuchs, C. & Theis, F.J.: Bayesian blind source separation for data with network structure. J. Comput. Biol. 21, 855-865 (2014)
198.
Illner, K. ; Fuchs, C. & Theis, F.J.: Bayesian blind source separation applied to the lymphocyte pathway. In: Gillli, M.* ; Gonzalez-Rodriguez, G.* ; Nieto-Reyes, A.* [Eds.]: Proccedings (21st International Conference on Computational Statistics (COMPSTAT2014), 19-22 August 2014, Geneva, Switzerland). 2014. 625-632
199.
Illner, K. ; Fuchs, C. & Theis, F.J.: Single-cell analysis: Biology at high resolution. Sep. Sci. Appl. 34, 24-26 (2014)
200.
Illner, K. ; Fuchs, C. & Theis, F.J.: Einzelzellanalysen: Biologie in Hochauflösung. GIT Fachz. Lab. 9, 28-30 (2014)