A GPU-Based Implementation of Differential Evolution for Solving the Gene Regulatory Network Model Inference Problem
CINVESTAV-IPN (Evolutionary Computation Group), Department of Computer Science, Av. IPN No. 2508, Col San Pedro Zacatenco, Mexico City, Mexico
Fourth International Workshop on Parallel Architectures and Bioinspired Algorithms (WPABA), 2011
@inproceedings{RamirezChavez2011gpu,
author={L. E. {Ramirez-Chavez} and C. A. {Coello Coello} and E. {Rodriguez-Tello}},
month={October},
year={2011},
title={A GPU-Based Implementation of Differential Evolution for Solving the Gene Regulatory Network Model Inference Problem},
booktitle={Proceedings of the Fourth International Workshop on Parallel Architectures and Bioinspired Algorithms, WPABA 2011},
pages={21–30},
address={Galveston Island, TX, USA}
}
In this paper, we present what we believe to be the first GPU-based implementation (using CUDA) for solving the gene regulatory network model inference problem. Our implementation uses differential evolution as its search engine, and adopts a power law system of differential equations (an S-System) for modelling the dynamics of the gene regulatory networks of our interest. Our preliminary results indicate that the use of GPUs produces an important reduction in the computational times required to solve this costly optimization problem. This could bring important benefits in Bioinformatics because of the many practical applications that the solution of this problem has.
January 23, 2012 by hgpu
