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arXiv · 2106.06580

Revealing the canalizing structure of Boolean functions: Algorithms and applications

Elena Dimitrova·Brandilyn Stigler·Claus Kadelka·David Murrugarra
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Abstract

Boolean functions can be represented in many ways including logical forms, truth tables, and polynomials. Additionally, Boolean functions have different canonical representations such as minimal disjunctive normal forms. Other canonical representation is based on the polynomial representation of Boolean functions where they can be written as a nested product of canalizing layers and a polynomial that contains the noncanalizing variables. In this paper we study the problem of identifying the canalizing layers format of Boolean functions. First, we show that the problem of finding the canalizing layers is NP-hard. Second, we present several algorithms for finding the canalizing layers of a Boolean function, discuss their complexities, and compare their performances. Third, we show applications where the computation of canalizing layers can be used for finding a disjunctive normal form of a nested canalizing function. Another application deals with the reverse engineering of Boolean networks with a prescribed layering format. Finally, implementations of our algorithms in Python and in the computer algebra system Macaulay2 are available at https://github.com/ckadelka/BooleanCanalization.

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Elena Dimitrova, Brandilyn Stigler, Claus Kadelka, David Murrugarra. 2021-06-11. Revealing the canalizing structure of Boolean functions: Algorithms and applications. https://doi.org/10.1016/j.automatica.2022.110630

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