Teams in this computational unit study several aspects of the cancer pathology through observation of the underlying molecular and cellular mechanisms: initiation (etiology, through the modelling of gene and environment interaction), development and tumor progression (inferring and modelling the gene and protein networks involved, analysis of phenotypes through bioimaging), and improvement in therapeutic strategies (diagnosis, prognosis, design and analysis of clinical trials, identification of therapeutic targets, virtual selection of therapeutic molecules).
Research projects are conducted in close collaboration with biologists and clinicians and always involved a mix of experimental and theoretical approaches, in iterative cycles from the wet biology to the mathematical model and back, which ultimately lead to validated and thus predictive models. They take advantage of new high throughput biological technologies at both the molecular and cellular levels (spectrometry, microarrays, high-throughput cellular phenotyping, deep sequencing) and use state-of-the-art and innovative methods of data integration and systems biology, statistical analysis, high dimension statistical learning, study of complexity, network modeling, virtual screening and bioimaging.