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The Dynamics of Canalizing Boolean Networks [PDF]
Complexity, 2020 Boolean networks are a popular modeling framework in computational biology to capture the dynamics of molecular networks, such as gene regulatory networks.
Elijah Paul +3 more
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The basis of easy controllability in Boolean networks [PDF]
Nature Communications, 2021 Boolean networks allow a simplified representation of interactions. Here, the authors systematically analyze regulation in dozens of biological Boolean networks, finding mathematical regularities that suggest biological systems could be controlled ...
Enrico Borriello, Bryan C. Daniels
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On the Lyapunov Exponent of Monotone Boolean Networks †
Mathematics, 2020 Boolean networks are discrete dynamical systems comprised of coupled Boolean functions. An important parameter that characterizes such systems is the Lyapunov exponent, which measures the state stability of the system to small perturbations.
Ilya Shmulevich
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Random Networks with Quantum Boolean Functions
Mathematics, 2021 We propose quantum Boolean networks, which can be classified as deterministic reversible asynchronous Boolean networks. This model is based on the previously developed concept of quantum Boolean functions.
Mario Franco +3 more
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Influence maximization in Boolean networks [PDF]
Nature Communications, 2022 Boolean networks modelling various biological processes are characterized by nonlinear reversible dynamics that makes their control challenging. The authors introduce extended concepts of influence and control, typically considered in the study of ...
Thomas Parmer +2 more
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Analytical approach of synchronous and asynchronous update schemes applied to solving biological Boolean networks. [PDF]
PLoS ONECharacterizing the minimum, necessary and sufficient components to generate the dynamics of a biological system has always been a priority to understand its functioning.
Antonio Bensussen +3 more
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Review and assessment of Boolean approaches for inference of gene regulatory networks
Heliyon, 2022 Boolean descriptions of gene regulatory networks can provide an insight into interactions between genes. Boolean networks hold predictive power, are easy to understand, and can be used to simulate the observed networks in different scenarios.We review ...
Žiga Pušnik +3 more
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An Evaluation of Methods for Inferring Boolean Networks from Time-Series Data. [PDF]
PLoS ONE, 2013 Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in ...
Natalie Berestovsky, Luay Nakhleh
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An ASP-based Approach for Attractor Enumeration in Synchronous and Asynchronous Boolean Networks [PDF]
Electronic Proceedings in Theoretical Computer Science, 2019 Boolean networks are conventionally used to represent and simulate gene regulatory networks. In the analysis of the dynamic of a Boolean network, the attractors are the objects of a special attention.
Tarek Khaled, Belaïd Benhamou
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An attractor-based complexity measurement for Boolean recurrent neural networks. [PDF]
PLoS ONE, 2014 We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics.
Jérémie Cabessa, Alessandro E P Villa
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