Open AccessSimulation of Scale Free Gene Regulatory Networks based on Threshold Functions on GPU
Author(s) -
Raphael R. Campos,
Ricardo Ferreira,
Julio C. Goldner Vendramini,
Fábio Vergara Cerqueira,
Marcelo L. Martins
Publication year - 2011
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/wscad.2011.17271
Subject(s) - computer science , boolean network , and inverter graph , theoretical computer science , graph , boolean function , graphics , boolean model , boolean expression , simple (philosophy) , standard boolean model , algorithm , discrete mathematics , mathematics , philosophy , computer graphics (images) , epistemology
Gene regulatory networks have been used to study diseases and cell evolution, where Random Boolean graphs are one of computational approaches. A Boolean graph is a simple and effective model, and its dynamic behavior has been used in several works. This article proposes an efficient environment to simulate Boolean graph on GPU (Graphics Processing Units). The dynamic behavior of a Boolean graph is computed by visiting the whole or a subset of state space. The proposed tool is based on statistical approaches to evaluate large graphs. Moreover, it can take into account scale free graphs with threshold functions. The experimental results show a speed-up factor of up to 40 times. In addition, the exploration of state spaces three orders of magnitude greater than previous approaches have been evaluated.