Systems biology has developed enormously over the 10 last years, with studies covering diverse biological levels (molecule, network, tissue, organism, ecology…). From an evolutionary point of view, systems biology provides unequalled opportunities. This thesis describes new methodologies and tools to study the evolution of biological systems, taking into account the multidimensional properties of biological parameters associated with multiple levels. Thus it addresses the clear need for novel methodologies specifically adapted to high-throughput evolutionary systems biology studies. By taking account the multi-level aspects of biological systems, this work highlight new evolutionary trends associated with both intra and inter-process constraints. In particular, this thesis includes (i) the development of an algorithm and a bioinformatics tool dedicated to comprehensive orthology inference and analysis for hundreds of species, (ii) the development of an original formalism for the integration of multi-scale variables allowing the synthetic representation of the evolutionary history of a given gene, (iii) the combination of this integrative tool with mathematical knowledge discovery approaches in order to highlight evolutionary perturbations in documented human biological systems (metabolic and signalling pathways...).
