Cycles generated by sequential iterations
Discrete Applied Mathematics
Regular Article: Solution of the Boolean Markus驴Yamabe Problem
Advances in Applied Mathematics
Necessary conditions for multistationarity in discrete dynamical systems
Discrete Applied Mathematics
Note: Comparison between parallel and serial dynamics of Boolean networks
Theoretical Computer Science
Positive circuits and maximal number of fixed points in discrete dynamical systems
Discrete Applied Mathematics
A Reduction of Logical Regulatory Graphs Preserving Essential Dynamical Properties
CMSB '09 Proceedings of the 7th International Conference on Computational Methods in Systems Biology
Decision diagrams for the representation and analysis of logical models of genetic networks
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Stochasticity in reactions: a probabilistic Boolean modeling approach
Proceedings of the 8th International Conference on Computational Methods in Systems Biology
Abstract Interpretation of Dynamics of Biological Regulatory Networks
Electronic Notes in Theoretical Computer Science (ENTCS)
Local negative circuits and fixed points in non-expansive Boolean networks
Discrete Applied Mathematics
Incorporating time delays into the logical analysis of gene regulatory networks
CMSB'06 Proceedings of the 2006 international conference on Computational Methods in Systems Biology
Positive and negative circuits in discrete neural networks
IEEE Transactions on Neural Networks
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Boolean networks are discrete dynamical systems extensively used to model biological regulatory networks. The dynamical analysis of these networks suffers from the combinatorial explosion of the state space, which grows exponentially with the number n of components. To face this problem, a classical approach consists in deducing from the interaction graph of the network, which only contains n vertices, some information on the dynamics of the network. In this paper, we present results in this topic, mainly by focusing on the influence of positive and negative feedbacks.