Network approaches for human diseases

Networks are scaling-up the analysis of gene and protein functions, hence offering new avenues to study the diseases in which these genes and proteins are involved. In the first part of my talk, I will focus on the exploration of interactome networks containing thousands of physical and functional interactions between proteins. We develop partitioning algorithms to recover community - or functional modules - from these large-scale networks, and use them to study the cellular functions of proteins of interest. We proposed for instance the involvement of Hsp27, a key stress-response protein, in DNA repair and splicing. We have recently extended the community detection to multiplex networks, i.e. networks containing different layers representing different interaction categories, such as protein-protein interaction or gene co-expression.

In the second part of my talk, I will present our ongoing work, which aims to contextualize networks and set up dynamic analyses to study prostate cancer progression to resistance. We proceed through proteomics data integration into large-scale static networks and dynamic models. Finally, I will describe how network models of cell signalling can be used to predict relevant drug synergies in gastric cancers.