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PuSH - Publikationsserver des Helmholtz Zentrums München

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1.
Glauche, I.* & Marr, C.: Mechanistic models of blood cell fate decisions in the era of single-cell data. Curr. Opin. Syst. Biol. 28, 100355 (2021)
2.
Hetzel, L. ; Fischer, D.S. ; Günnemann, S.* & Theis, F.J.: Graph representation learning for single cell biology. Curr. Opin. Syst. Biol. 28:100347 (2021)
3.
Lakrisenko, P. & Weindl, D.: Dynamic models for metabolomics data integration. Curr. Opin. Syst. Biol. 28:100358 (2021)
4.
Loos, C. & Hasenauer, J.: Mathematical modeling of variability in intracellular signaling. Curr. Opin. Syst. Biol. 16, 17-24 (2019)
5.
Colomé-Tatché, M. & Theis, F.J.: Statistical single cell multi-omics integration. Curr. Opin. Syst. Biol. 7, 54-59 (2018)
6.
Angerer, P. et al.: Single cells make big data: New challenges and opportunities in transcriptomics. Curr. Opin. Syst. Biol. 4, 85-91 (2017)
7.
Falter-Braun, P. & Calderwood, M.A.*: Big data biology - just the next big hype? Curr. Opin. Syst. Biol. 4, iv-vi (2017)
8.
Maier, H. ; Leuchtenberger, S. ; Fuchs, H. ; Gailus-Durner, V. & Hrabě de Angelis, M.: Big data in large-scale systemic mouse phenotyping. Curr. Opin. Syst. Biol. 4, 97-104 (2017)
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