Symmetry Properties of Nested Canalyzing Functions

Abstract

Many researchers have studied symmetry properties of various Boolean functions. A class of Boolean functions, called nested canalyzing functions (NCFs), has been used to model certain biological phenomena. We identify some interesting relationships between NCFs, symmetric Boolean functions and a generalization of symmetric Boolean functions, which we call $r$-symmetric functions (where $r$ is the symmetry level). Using a normalized representation for NCFs, we develop a characterization of when two variables of an NCF are symmetric. Using this characterization, we show that the symmetry level of an NCF $f$ can be easily computed given a standard representation of $f$. We also present an algorithm for testing whether a given $r$-symmetric function is an NCF. Further, we show that for any NCF $f$ with $n$ variables, the notion of strong asymmetry considered in the literature is equivalent to the property that $f$ is $n$-symmetric. We use this result to derive a closed form expression for the number of $n$-variable Boolean functions that are NCFs and strongly asymmetric. We also identify all the Boolean functions that are NCFs and symmetric.

17 pages

References in corpus (6)

• Random Boolean Network Models and the Yeast Transcriptional Network
• Genetic networks with canalyzing Boolean rules are always stable
• Boolean nested canalizing functions: a comprehensive analysis
• The Influence of Canalization on the Robustness of Boolean Networks
• Sensitivity and block sensitivity of nested canalyzing function
• Nested Canalyzing Functions And Their Average Sensitivities