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.

Nobile, M., Mauri, G. (2013). Evolutionary inference of biochemical reaction networks accelerated on graphics processing units. In 2013 International Conference on High Performance Computing & Simulation (HPCS) (pp.668-670). IEEE [10.1109/HPCSim.2013.6641490].

Evolutionary inference of biochemical reaction networks accelerated on graphics processing units

NOBILE, MARCO SALVATORE;MAURI, GIANCARLO
2013

Abstract

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.
slide + paper
Systems Biology, GPU, Genetic Programming, Particle Swarm Optimization
English
High Performance Computing and Simulation (HPCS), 2013
2013
2013 International Conference on High Performance Computing & Simulation (HPCS)
978-1-4799-0838-7
lug-2013
668
670
none
Nobile, M., Mauri, G. (2013). Evolutionary inference of biochemical reaction networks accelerated on graphics processing units. In 2013 International Conference on High Performance Computing & Simulation (HPCS) (pp.668-670). IEEE [10.1109/HPCSim.2013.6641490].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/48376
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