Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
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Section: New Results

Dynamics of evolutionary innovation

Using a combination of mathematical and computational models (NK-Fitness-Landscapes and Aevol), we investigated the dynamics of innovation in evolving systems. We showed that innovation is often triggered by specific mutational events, typically structural variation of the genome (e.g. duplications, inversions, …). We further studied this effect and showed that innovation is due to the differences of time scale between the different kinds of mutations: fast mutations (typically point mutations) are rapidly exhausted, resulting in a fitness plateau. However, slow mutations (typically structural variations) can open new evolutionary paths, resulting in the population escaping from the fitness plateau. An article is in preparation in collaboration with Santiago F. Elena (CSIC, Spain).