Our focus
In the Computational Cancer Genomics Group, we are interested in gene regulation in both healthy and diseased cells. Breakthroughs in genomics technologies have led to the production of large volumes of data that could potentially tell us something about how gene regulatory instructions are encoded in our DNA. Our group develops new algorithms, computer programs, web services and databases that will help us and others to extract knowledge and understanding from such data. We also collaborate with experimental biologists on interdisciplinary projects and organize postgraduate courses in genomic data analysis.
The group develops the EPD tool.
Main publications 2020
- Ambrosini G et al.
Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study
Genome Biol, doi: 10.1186/s13059-020-01996-3 - Meylan P et al.
EPD in 2020: enhanced data visualization and extension to ncRNA promoters
Nucleic Acids Res, doi: 10.1093/nar/gkz1014 - Ataca D et al.
The secreted protease Adamts18 links hormone action to activation of the mammary stem cell niche
Nat Commun, doi: 10.1038/s41467-020-15357-y
Main publications 2019
- Groux R and Bucher P.
SPar-K: a method to partition NGS signal data
Bioinformatics, doi: 10.1093/bioinformatics/btz416 - Kubik S et al.
Opposing chromatin remodelers control transcription initiation frequency and start site selection
Nat Struct Mol Biol, doi: 10.1038/s41594-019-0273-3 - Delaneau O et al.
Chromatin three-dimensional interactions mediate genetic effects on gene expression
Science, doi: 10.1126/science.aat8266
Find out more about the Group’s activities
