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Stratification and enumeration of Boolean functions by canalizing depth

Authors: Qijun He; Matthew Macauley;

Stratification and enumeration of Boolean functions by canalizing depth

Abstract

Boolean network models have gained popularity in computational systems biology over the last dozen years. Many of these networks use canalizing Boolean functions, which has led to increased interest in the study of these functions. The canalizing depth of a function describes how many canalizing variables can be recursively picked off, until a non-canalizing function remains. In this paper, we show how every Boolean function has a unique algebraic form involving extended monomial layers and a well-defined core polynomial. This generalizes recent work on the algebraic structure of nested canalizing functions, and it yields a stratification of all Boolean functions by their canalizing depth. As a result, we obtain closed formulas for the number of n-variable Boolean functions with depth k, which simultaneously generalizes enumeration formulas for canalizing, and nested canalizing functions.

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Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), Enumeration, Extended monomial layer, Nested canalizing function, canalizing function, FOS: Physical sciences, nested canalizing function, enumeration, canalizing depth, Biological Physics (physics.bio-ph), Switching theory, application of Boolean algebra; Boolean functions, Boolean function, extended monomial layer, FOS: Mathematics, Mathematics - Combinatorics, Canalizing depth, Physics - Biological Physics, Combinatorics (math.CO), Canalizing function, Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Top 10%
Green
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