Evolutionary systems biology

Our research is focused on the management of the ubiquitous "data overload" from today's high throughput technologies. We use complementary bottom-up and top-down approaches to study the behaviour and evolution of biological systems, such as “hyperstructures” (macromolecular complexes, organelles, viruses…) or biological networks (metabolic, transcriptional, interaction as well as developmental or disease-related networks…). In the bottom-up approach, we study basic components and integrate the data to detect relevant patterns (e.g., proteins and their interactions in a complex). In the top-down approach, we establish our knowledge of the system, and attempt to disassemble it, e.g. to study normal and abnormal (disease) processes. This involves the development of:

• Original algorithms and software based on an evolutionary approach to analyse hierarchical systems in the light of their conservation and distribution in eukarya,

• New data system architectures suitable for computer and data grids to allow rapid retrieval, organisation and exploration of raw data and information and to extract hidden knowledge,

• Bioinformatics pipelines for quality control, integration, analysis and real time maintenance of interconnected genomics data with the goal of understanding disease origins and identifying and developing new therapeutic targets.

SHAPING THE FUTURE !

Addressing the complexity of biological systems will involve automatic value-added data processing and analysis, requiring extensive computational power as well as rapid access to dispersed but synchronized data resources. In this context, our research will focus on the development of original bioinformatics solutions deployed on advanced computer and data technologies to ensure automated, updated and sustained analyses. Our comparison and modelling of biological systems will take advantage of the postulate that in living systems, “what is important is generally conserved”: i.e., billions of years of evolution and selection constitute a discriminating filter and a unique source of information for interpreting what the new data actually mean, and how they can be used to address questions that need to be answered.