The Markowetz lab develops algorithms and statistics to leverage complex and heterogeneous data sources for biomedical research. Our main research question is: How do perturbations to cellular networks shape phenotypes?
Research
Natural perturbations like copy number alterations and SNPs can promote cancer development. With our partners at CRI we aim to characterize disruptions of signaling pathways in tumours and to identify genomic alterations that drive tumour evolution.
Experimental perturbations like RNAi are key approaches at the forefront of functional genomics. With international collaboration partners we work on methods to identify signaling pathways and their re-wiring from downstream effects of gene perturbations.
Events
- We co-organize an ESF exploratory workshop 'From phenotypes to pathways' in Sept 2010
- We co-organize a Cancer Bioinformatics Workshop in Sept 2010 at CRI.
- Florian taught a tutorial at ISMB 2010 on gene perturbation analysis.
Publications
- How to understand the cell by breaking it: network analysis of gene perturbation screens
F. Markowetz, PLoS Comp Bio 2010 6(2). [ PMID:20195495 ] - Systems-level dynamic analyses of fate change in murine embryonic stem cells. R. Lu, F. Markowetz, et al. Nature 2009; 462(7271):358-362
[ PMID:19924215 ] - Structure Learning in Nested Effects Models. A. Tresch, F. Markowetz. Statistical Applications in Genetics and Molecular Biology: Vol. 7: Iss. 1, Article 9, 2008. [ PMID:18312214 ]
Software
- nem - an R/Bioconductor package to infer Nested Effects Models
- dyNet - dynamic network visualization and inference
- HTSanalyzeR - network analysis of high-throughput screens
