Publications by authors named "H Hazgui"

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.

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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.

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The French school of theoretical biology has been mainly initiated in Poitiers during the sixties by scientists like J. Besson, G. Bouligand, P.

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The problem of stability in population dynamics concerns many domains of application in demography, biology, mechanics and mathematics. The problem is highly generic and independent of the population considered (human, animals, molecules,…). We give in this paper some examples of population dynamics concerning nucleic acids interacting through direct nucleic binding with small or cyclic RNAs acting on mRNAs or tRNAs as translation factors or through protein complexes expressed by genes and linked to DNA as transcription factors.

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MicroRNAs are non-coding parts of nuclear and mitochondrial genomes, preventing the weakest part of the genetic regulatory networks from being expressed and preventing the appearance of a too many attractors in these networks. They have also a great influence on the chromatin clock, which ensures the updating of the genetic regulatory networks. The post-transcriptional inhibitory activity by the microRNAs, which is partly unspecific, is due firstly to their possibly direct negative action during translation by hybridizing tRNAs, especially those inside the mitochondrion, hence slowing mitochondrial respiration, and secondly to their action on a large number of putative m-RNA targets like those involved in immunetworks; We show that the circuits in the core of the interaction graphs are responsible for the small number of dedicated attractors that correspond to genetically controlled functions, partly due to a general filtering by the microRNAs.

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