Statistical detection of boolean regulatory relationships. Academic Article uri icon


  • A statistic tool for the detection of multivariate Boolean relationships is presented, with applications in the inference of gene regulatory mechanisms. A statistical test is developed for the detection of a nonzero discrete coefficient of determination (CoD) between predictor and target variables. This is done by framing the problem in the context of a stochastic logic model that naturally allows the inclusion of prior knowledge if available. The rejection region, p-value, statistical power, and confidence interval are derived and analyzed. Furthermore, the issue of multiplicity of tests due to presence of numerous candidate genes and logic relationships is addressed via FWER- and FDR-controlling approaches. The methodology is demonstrated by experiments using synthetic data and real data from a study on ionizing radiation (IR)-responsive genes. The results indicate that the proposed methodology is a promising tool for detection of gene regulatory relationships from gene-expression data. Software that implements the COD test is available online as an R package.

published proceedings

  • IEEE/ACM Trans Comput Biol Bioinform

altmetric score

  • 3

author list (cited authors)

  • Chen, T., & Braga-Neto, U. M.

citation count

  • 4

complete list of authors

  • Chen, Ting||Braga-Neto, Ulisses M

publication date

  • September 2013