SFB 1243 Cancer Evolution

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Theis, Fabian J.

Prof. Dr. Fabian Theis

Helmholtz Zentrum München, Institute of Computational Biology


Helmholtz Zentrum München
Institute of Computational Biology
Ingolstädter Landstr. 1
85764 Neuherberg

Phone: +49 (0)89 3187-4030

Website: Machine Learning Group
Website: Institute of Computational Biology

Work group

A17 Computational models of neoplasmic heterogeneities and lineage choice

10 Major publications related to project

(See publications for recent papers published in the SFB context since 2016)

Buettner F, Natarajan KN, Casale FP, Proserpio V, Scialdone A, Theis FJ, Teichmann SA, Marioni JC and Stegle O (2015). Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. Biotechnol., 33, 155-160.

Haghverdi L, Buettner F and Theis FJ (2015). Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics, 2015 May 21. [Epub ahead of print]

Moignard V, Woodhouse S, Haghverdi L, Lilly AJ, Tanaka Y, Wilkinson AC, Buettner F, Macaulay IC, Jawaid W, Diamanti E, Nishikawa S, Piterman N, Kouskoff N, Theis FJ, Fisher J and Göttgens B (2015). Decoding the regulatory network of early blood development from single-cell gene expression measurements. Nat. Biotechnol., 33, 269-76.

Ocone A, Haghverdi L, Mueller N and Theis FJ (2015). Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data. Bioinformatics, 31, i89-i.96.

Bajikar SS, Fuchs C, Roller A, Theis FJ and Janes KA (2014). Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles. PNAS, 111, E626-E636.

Buettner F, Moignard V, Göttgens B and Theis FJ (2014). Probabilistic PCA of censored data: Accounting for uncertainties in the visualisation of high-throughput single-cell qPCR data. Bioinformatics, 30, 1867-1875.

Hasenauer J, Hasenauer C, Hucho T and Theis FJ (2014). ODE constrained mixture modelling: A method for unraveling subpopulation structures and dynamics. PLoS Comput. Biol., 2014, 10, e1003686

Moignard V, Macaulay IC, Swiers G, Buettner F, Schütte J, Calero-Nieto FJ, Kinston S., Joshi A, Hannah R, Theis FJ, Jacobsen SE, de Bruijn MF and Göttgens B (2013). Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis. Nat. Cell Biol., 15, 363-372.

Sass S, Buettner F, Mueller N and Theis FJ (2013). A modular framework for gene set analysis integrating multilevel omics data. Nucleic Acids Res., 41, 9622-9633.

Buettner F and Theis FJ (2012). A novel approach for resolving differences in single-cell gene expression patterns from zygote to blastocyst. Bioinformatics, 28, i626-i632.