Results 11 to 20 of about 140,409 (275)
Evolving sensitivity balances Boolean Networks. [PDF]
PLoS ONE, 2012 We investigate the sensitivity of Boolean Networks (BNs) to mutations. We are interested in Boolean Networks as a model of Gene Regulatory Networks (GRNs). We adopt Ribeiro and Kauffman's Ergodic Set and use it to study the long term dynamics of a BN. We
Jamie X Luo, Matthew S Turner
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Classification of Random Boolean Networks [PDF]
, 2002 We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of
Gershenson, Carlos
core +7 more sources
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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Reducing Boolean Networks with Backward Boolean Equivalence [PDF]
, 2021 Boolean Networks (BNs) are established models to qualitatively describe biological systems. The analysis of BNs might be infeasible for medium to large BNs due to the state-space explosion problem. We propose a novel reduction technique called \emph{Backward Boolean Equivalence} (BBE), which preserves some properties of interest of BNs.
Georgios Argyris +4 more
openaire +4 more sources
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
doaj +1 more source
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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Parallel One-Step Control of Parametrised Boolean Networks
Mathematics, 2021 Boolean network (BN) is a simple model widely used to study complex dynamic behaviour of biological systems. Nonetheless, it might be difficult to gather enough data to precisely capture the behavior of a biological system into a set of Boolean functions.
Luboš Brim +3 more
doaj +1 more source
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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