Structuring a gene network using a multiresolution independence test

In order to structure a gene network, a score-based approach is often used. A score-based approach, however, is problematic because by assuming a probability distribution, one is prevented from finding other dependent relationships with other genes. In this research, we structured a gene network from observed gene expression data using a multiresolution independence test and a conditional independence test, which is the non-parametric method proposed by Margaritis for learning the structure of Bayesian networks without making any probability distribution assumptions. The experimental results achieved an improvement in sensitivity of 0.05, and

• Type: Conference
• Year: 2010
• Where: ICASSP
• Authors: Takayuki Yamamoto, Tetsuya Takiguchi, Yasuo Ariki
• Keywords: Gene Network, ICASSP 2010, Probability Distribution, Score-based Approach, Signal Processing