bioRxivBiophysics
The Influence of Canalization on the Robustness of Boolean Networks
Abstract
Time- and state-discrete dynamical systems are frequently used to model molecular networks. This paper provides a collection of mathematical and computational tools for the study of robustness in Boolean network models. The focus is on networks governed by k-canalizing functions, a recently introduced class of Boolean functions that contains the well-studied class of nested canalizing functions. The activities and sensitivity of a function quantify the impact of input changes on the function output. This paper generalizes the latter concept to c-sensitivity and provides formulas for the activities and c-sensitivity of general k-canalizing functions as well as canalizing functions with more precisely defined structure. A popular measure for the robustness of a network, the Derrida value, can be expressed as a weighted sum of the c-sensitivities of the governing canalizing functions, and can also be calculated for a stochastic extension of Boolean networks. These findings provide a computationally efficient way to obtain Derrida values of Boolean networks, deterministic or stochastic, that does not involve simulation.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Choices of regulatory logic class modulate the dynamical regime in random Boolean networks
Priyotosh Sil, Suchetana Mitra, … Areejit Samal·Chaos Solitons & FractalsPeer-reviewed·Mar 13, 2025
- Minimum complexity drives regulatory logic in Boolean models of living systems
Ajay Subbaroyan, Olivier Martin, Areejit Samal·PNAS NexusPeer-reviewed·Mar 1, 2022
- Degeneracy measures in biologically plausible random Boolean networks
Basak Kocaoglu, William Alexander·BMC BioinformaticsPeer-reviewed·Feb 14, 2022
- DReSS: A difference measurement based on reachability between state spaces of Boolean networks
Ziqiao Yin, Binghui Guo, … Zhiming Zheng·Briefings in BioinformaticsPeer-reviewed·Oct 17, 2020
- Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph
Priyotosh Sil, Ajay Subbaroyan, … Areejit Samal·Briefings in BioinformaticsPeer-reviewed·Mar 27, 2024
- Preponderance of generalized chain functions in reconstructed Boolean models of biological networks
Suchetana Mitra, Priyotosh Sil, … Areejit Samal·Scientific ReportsPeer-reviewed·Mar 20, 2024