Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10351616 | Computers in Biology and Medicine | 2011 | 8 Pages |
Abstract
Bayesian network (BN) has been successfully used to infer the regulatory relationships of genes from microarray dataset. However, one major limitation of BN approach is the computational cost because the calculation time grows more than exponentially with the dimension of the dataset. In this paper, we propose a sub-space greedy search method for efficient Bayesian Network inference. Particularly, this method limits the greedy search space by only selecting gene pairs with higher partial correlation coefficients. Using both synthetic and real data, we demonstrate that the proposed method achieved comparable results with standard greedy search method yet saved â¼50% of the computational time. We believe that sub-space search method can be widely used for efficient BN inference in systems biology.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Qing Zhang, Yong Cao, Yong Li, Yanming Zhu, Samuel S.M. Sun, Dianjing Guo,