Entropy as a Robustness Marker in Genetic Regulatory Networks.

Genetic regulatory networks have evolved by complexifying their control systems with numerous effectors (inhibitors and activators). That is, for example, the case for the double inhibition by microRNAs and circular RNAs, which introduce a ubiquitous double brake control reducing in general the number of attractors of the complex genetic networks (e.g.

Biological Networks Entropies: Examples in Neural Memory Networks, Genetic Regulation Networks and Social Epidemic Networks.

Networks used in biological applications at different scales (molecule, cell and population) are of different types: neuronal, genetic, and social, but they share the same dynamical concepts, in their continuous differential versions (e.g., non-linear Wilson-Cowan system) as well as in their discrete Boolean versions (e.

Ten-year follow-up of cluster-based asthma phenotypes in adults. A pooled analysis of three cohorts.

Rationale: The temporal stability of adult asthma phenotypes identified using clustering methods has never been addressed. Longitudinal cluster-based methods may provide novel insights in the study of the natural history of asthma.

Objectives: To compare the stability of cluster-based asthma phenotype structures a decade apart in adults and to address the individuals' phenotypic transition across these asthma phenotypes.