Evolutionary inference of biochemical reaction networks accelerated on graphics processing units

The reverse engineering (RE) of biochemical reaction networks is a fundamental and very complex task in Systems Biology. My PhD thesis is focused on the definition of an automatic RE methodology based on the fusion of Genetic Programming and Particle Swarm Optimization. The methodology I propose relies on the execution of a massive number of simulations, whose computational costs are relevant. To the aim of reducing the overall running time, I am implementing the methodology on a parallel architecture, namely, Nvidia´s CUDA.