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Resting-state functional connectivity (RSFC) studies considering pairwise linear correlations have attracted great interests while the underlying functional network structure still remains poorly understood. To further our understanding of RSFC, this paper presents an analysis of the resting-state networks (RSNs) based on the steady-state distributions and provides a novel angle to investigate the...
Fine-scale models based on stochastic differential equations can provide the most detailed description of the dynamics of gene expression and imbed, in principle, all the information about the biochemical reactions involved in gene interactions. However, the computational complexity involved in the design of optimal intervention strategies to favorably effect system dynamics for such detailed models...
This article presents a tutorial survey of some of the recent results on intervention in the context of probabilistic gene regulatory networks, which, owing to their original binary formulation and their usual application using binary and ternary gene-expression quantization, are generically called probabilistic Boolean networks (PBNs). These are essentially probabilistic generalizations of the standard...
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