We are specifically focusing on trying to bridge together signaling pathways and metabolism through the development of models integrating metabolomic, proteomic and phosphoproteomic data. In order to do so, we are building resources that account for signaling/metabolic pathways crosstalks and build mechanistic models integrating these layers. This will also be achieved through collaborations with wet lab experimentalist able to generate dataset accounted for proteomic, phosphoproteomic and metabolomics in parallel. We will also expand tools developed by our team such as CellNopt or PHONEMeS to train mechanistic models using trans-omic resources and experimental dataset. These models will allow getting better insights into the characteristics of signaling and metabolic pathways, and will be used to perform predictions of relevant drug targets in the context of cancer and metabolic diseases.
Research in this area is partially funded by the European H2020 MCSA Innovative Training Network SyMBioSys.
Gonçalves et al Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models. Molecular bioSystems Volume 9 (2013) p.1576-1583