Using experimentation, computation and theory, we characterize the influence of genomic variation in populations, patients or cells on patient phenotypes like relapse or survival and intermediate phenotypes like gene expression or tissue architecture.

cancer genome cancer tissue cancer mechanism network biology

We analyze the functional impact of genomic changes and reconstruct the evolutionary history of tumours.

To put genomics in a tissue context we integrate quantita- tive tissue pheno- types with paired genomic profiles.

We investigate the genetic and protein factors that deter- mine the binding dynamics of nuclear receptors.

We develop comp- utational and stat- istical methods to visualize, analyze and reconstruct biological networks.



  • Schwarz et al (2014), Phylogenetic quantification of intra-tumour heterogeneity, PLoS Comp Bio 10(4)
  • Trinh et al (2014), GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images, Genome Biology, 15:442
  • Fletcher et al (2013), Master regulators of FGFR2 signalling and breast cancer risk, Nature Commun 4:2464
  • Yuan et al (2012), Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling, Science Transl Med 4

... more publications


  • Bitphylogeny - Bayesian framework for intra-tumour phylogenies
  • CRImage - tumour tissue analysis
  • GoIFISH - quantify single cell heterogeneity from IFISH images
  • MEDICC - intra-tumor copy-number comparisons
  • nem - inferring Nested Effects Models from downstream perturbation effects
  • RedeR - bridging the gap between statistical computing and network visualization

... more software


Florian Markowetz
University of Cambridge CRUK Cambridge Institute
Robinson Way
Cambridge, CB2 0RE, UK
p: +44 (0) 1223 769 628
f: +44 (0) 1223 769 510