An ambitious EC-funded research initiative on epigenetics advancing towards systems biology

We collaborate closely with genome biologist and develop new statistical methods and tools for the analysis of various type of genome-wide data. We are largely data- and problem-driven, and ultimately the methods we develop are catered to the characteristics of the technology platform generating the data. We develop publicly-available open-source software tools, generally through the Bioconductor project. Two main priorities for the group are the analysis of count data (e.g. RNA-seq, ChIP-seq; R/Bioconductor package 'edgeR') and the analysis and integration of epigenome datasets (e.g. DNA methylation from MBD-seq, BS-seq and Illumina 450k array; R/Bioconductor package 'Repitools'). Specifically, we are working on methods to carefully normalize and compare a wide range of epigenome datasets across conditions, and integrate them with other molecular profiles, such as copy number information and gene expression data.

List of postdocs/students with potential interest:

• Andrea Komljenovic
• Olga Nikolayeva
• Helen Lindsay
• Ian Morilla
• Gosia Nowicka