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61.
Benedetti, E. et al.: Network inference from glycoproteomics data reveals new reactions in the IgG glycosylation pathway. Nat. Commun. 8:1483 (2017)
62.
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)
63.
Budde, M.* et al.: Integrating polygenic allele burden information and phenomic data to characterize complex disease trajectories in severe mental illness. Eur. Neuropsychopharmacol. 27, 3, S406 (2017)
64.
Buggenthin, F. et al.: Prospective identification of hematopoietic lineage choice by deep learning. Nat. Methods, DOI: 10.1038/nmeth.4182 (2017)
65.
Chlis, N.-K. ; Wolf, F.A. & Theis, F.J.: Model-based branching point detection in single-cell data by K-Branches clustering. Bioinformatics 33, 3211-3219 (2017)
66.
Comes, A.* et al.: Polygenic burden analysis of longitudinal clusters of quality of life and functioning in patients with severe mental illness. Eur. Neuropsychopharmacol. 27, 3, S408-S409 (2017)
67.
Conlon, T.M. et al.: 2d cross-omics integrated enrichment analysis of human and mice COPD lungs reveal novel pathological mechanisms of disease progression. Am. J. Respir. Crit. Care Med. 195 (2017)
68.
Dirmeier, S.* ; Fuchs, C. ; Müller, N.S. & Theis, F.J.: netReg: Network-regularized linear models for biological association studies. Bioinformatics 34, 896-898 (2017)
69.
Eulenberg, P. et al.: Reconstructing cell cycle and disease progression using deep learning. Nat. Commun. 8:463 (2017)
70.
Florea, A.M.* et al.: Calcium-regulatory proteins as modulators of chemotherapy in human neuroblastoma. Oncotarget 8, 22876-22893 (2017)
71.
Fröhlich, F. ; Theis, F.J. ; Rädler, J.O.* & Hasenauer, J.: Parameter estimation for dynamical systems with discrete events and logical operations. Bioinformatics 33, 1049-1056 (2017)
72.
Fröhlich, F. ; Kaltenbacher, B.* ; Theis, F.J. & Hasenauer, J.: Scalable parameter estimation for genome-scale biochemical reaction networks. PLoS Comput. Biol. 13:e1005331 (2017)
73.
Garzorz-Stark, N. et al.: The imiquimod model as a model for psoriasis and/or eczema in humans? Exp. Dermatol. 26, E68-E68 (2017)
74.
Garzorz-Stark, N.* et al.: TLR7/8 agonists stimulate plasmacytoid dendritic cells to initiate a Th17-deviated acute contact dermatitis in humans. J. Invest. Dermatol. 137, S275-S275 (2017)
75.
Heilbronner, U.* et al.: The Role of micrornas in the course of servere mental disorders. Eur. Neuropsychopharmacol. 27, 3, S456-S457 (2017)
76.
Hilgendorff, A. et al.: Discrimination of pulmonary changes in neonatal chronic lung disease by a new Mri score. Am. J. Respir. Crit. Care Med. 195 (2017)
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Hilsenbeck, O.* et al.: fastER: A user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy. Bioinformatics 33, 2020-2028 (2017)
78.
Jagiella, N. ; Rickert, D. ; Theis, F.J. & Hasenauer, J.: Parallelization and high-performance computing enables automated statistical inference of multi-scale models. Cell Syst. 4, 194–206.e9 (2017)
79.
Kazeroonian, A. ; Theis, F.J. & Hasenauer, J.: A scalable moment-closure approximation for large-scale biochemical reaction networks. Bioinformatics 33, i293-i300 (2017)
80.
Krautenbacher, N. ; Theis, F.J. & Fuchs, C.: Correcting classifiers for sample selection bias in two-phase case-control studies. Comput. Math. Methods Med. 2017:7847531 (2017)