Quantifying the notions of canalizing and master genes in a gene regulatory network-a Boolean network modeling perspective. Academic Article uri icon

abstract

  • MOTIVATION: Canalizing genes enforce broad corrective actions on cellular processes for the purpose of biological robustness maintaining a constant phenotype to remain unchanged in spite of genetic mutations or environmental perturbations. Despite their central role in biological systems, the observation/detection of canalizing genes is often impeded because the behavior of affected genes is highly varied relative to the inactive canalizer. Therefore, the activity of canalizing genes is difficult to predict to any significant degree by their subject genes under normal cell conditions. RESULTS: We investigate this question and present a quantitative framework that allows for the estimation of the power of canalizing genes in the context of Boolean Networks (BNs) with perturbation. This framework borrows tools from the Pattern Recognition theory and uses the coefficient of determination (CoD) to capture the capacity of the canalizing genes. The canalizing power (CP) of a gene is quantitatively characterized by two terms: regulation power (RP) and incapacitating power (IP). We base this assumption on the idea that canalizing power of a gene should be quantified by the extent of its regulation on the overall network and the extent of control that the gene takes over from other master genes when it is activated, which is equivalent to reduction of the control of other master genes upon its activation. Following this, the CP concept is illustrated with examples in which the goal is to provide preliminary evidence that CP can be used to characterize the ability of canalizing genes. AVAILABILITY AND IMPLEMENTATION: A library of functions written in MATLAB for computing CP is available at http://github.com/eunjikim-angie/CanalizingPower.

altmetric score

  • 1.25

author list (cited authors)

  • Kim, E., Ivanov, I., & Dougherty, E. R.

citation count

  • 1

publication date

  • July 2018