Comptes Rendus
Dynamical Systems
Robustness in biological regulatory network III: Application to genetic networks controlling the morphogenesis
[Robustesse dans les réseaux de régulation biologique III : Applications biologiques aux réseaux génétiques contrôlant la morphogénèse]
Comptes Rendus. Mathématique, Volume 350 (2012) no. 5-6, pp. 289-292.

Cette Note utilise les notions mathématiques existant entre entropie et vitesse de retour à lʼéquilibre dans les graphes dʼinteraction des réseaux génétiques de manière générale, appliquées ici au cas particulier des réseaux de régulation génétique booléens probabilistes à seuil (appelés getBrens). Il est prouvé que, dans certaines circonstances de connectivité particulière, lʼentropie de la mesure invariante du système dynamique peut être considérée à la fois comme un indice de complexité et de stabilité, en montrant explicitement le lien existant entre ces deux notions fondamentales, afin de mieux caractériser la résistance dʼun système biologique à des perturbations endogènes ou exogènes, comme dans le cas des n-switches. Des exemples de réseaux sont ensuite traités, montrant lʼintérêt pratique des notions de complexité et stabilité introduites dans cet article. Ils concernent le contrôle de la morphogénèse.

This Note deals with the mathematical notions of entropy and stability rate in interaction graphs of genetic networks, in the particular context of the genetic threshold Boolean random regulatory networks (getBrens). It is proved that in certain circumstances of particular connectance, the entropy of the invariant measure of the dynamical system can be considered both as a complexity and a stability index, by exploiting the link between these two notions, fundamental to characterize the resistance of a biological system against endogenous or exogenous perturbations, as in the case of the n-switches. Examples of biological networks are then given showing the practical interest of the mathematical notions of complexity and stability in the case of the control of the morphogenesis.

Reçu le :
Accepté le :
Publié le :
DOI : 10.1016/j.crma.2012.01.002
Jacques Demongeot 1 ; Jules Waku 1, 2

1 AGIM CNRS/UJF 3405, Université J. Fourier Grenoble I, faculté de médecine, 38700 La Tronche, France
2 LIRIMA-UMMISCO, Université de Yaoundé, faculté des sciences, BP 812, Yaoundé, Cameroon
@article{CRMATH_2012__350_5-6_289_0,
     author = {Jacques Demongeot and Jules Waku},
     title = {Robustness in biological regulatory network {III:} {Application} to genetic networks controlling the morphogenesis},
     journal = {Comptes Rendus. Math\'ematique},
     pages = {289--292},
     publisher = {Elsevier},
     volume = {350},
     number = {5-6},
     year = {2012},
     doi = {10.1016/j.crma.2012.01.002},
     language = {en},
}
TY  - JOUR
AU  - Jacques Demongeot
AU  - Jules Waku
TI  - Robustness in biological regulatory network III: Application to genetic networks controlling the morphogenesis
JO  - Comptes Rendus. Mathématique
PY  - 2012
SP  - 289
EP  - 292
VL  - 350
IS  - 5-6
PB  - Elsevier
DO  - 10.1016/j.crma.2012.01.002
LA  - en
ID  - CRMATH_2012__350_5-6_289_0
ER  - 
%0 Journal Article
%A Jacques Demongeot
%A Jules Waku
%T Robustness in biological regulatory network III: Application to genetic networks controlling the morphogenesis
%J Comptes Rendus. Mathématique
%D 2012
%P 289-292
%V 350
%N 5-6
%I Elsevier
%R 10.1016/j.crma.2012.01.002
%G en
%F CRMATH_2012__350_5-6_289_0
Jacques Demongeot; Jules Waku. Robustness in biological regulatory network III: Application to genetic networks controlling the morphogenesis. Comptes Rendus. Mathématique, Volume 350 (2012) no. 5-6, pp. 289-292. doi : 10.1016/j.crma.2012.01.002. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2012.01.002/

[1] O. Cinquin; J. Demongeot Positive and negative feedback: striking a balance between necessary antagonists, J. Theoret. Biol., Volume 216 (2002), pp. 229-241

[2] O. Cinquin; J. Demongeot High-dimensional switches and the modeling of cellular differentiation, J. Theoret. Biol., Volume 233 (2005), pp. 391-411

[3] M. Cosnard; J. Demongeot Attracteurs: une approche déterministe, C. R. Acad. Sci. Paris, Ser. I, Volume 300 (1985), pp. 551-556

[4] M. Cosnard, J. Demongeot, On the definitions of attractors, in: Lectures Notes in Math., vol. 1163, 1985, pp. 23–31.

[5] M. Cosnard; E. Goles Discrete states neural networks and energies, Neural Networks, Volume 10 (1997), pp. 327-334

[6] M. Cosnard; J. Demongeot; K. Lausberg; K. Lott Attractors, confiners, and fractal dimensions. Applications in neuro-modelling, Grenoble, 1991 (Mathematical Biology), Wuerz, Winnipeg (1993), pp. 69-94

[7] J. Demongeot; S. Sené Asymptotic behavior and phase transition in regulatory networks. II Simulations, Neural Networks, Volume 21 (2008), pp. 971-979

[8] J. Demongeot; S. Sené The singular power of the environment on nonlinear Hopfield networks, Proceedings CMSBʼ11, ACM, New York, 2011, pp. 55-64

[9] J. Demongeot; J. Waku Robustness in biological regulatory networks I. Mathematical approach, C. R. Acad. Sci. Paris, Ser. I, Volume 350 (2012) no. 3–4, pp. 221-224 | DOI

[10] J. Demongeot; J. Waku Robustness in biological regulatory networks II. Application to genetic threshold Boolean random regulatory networks, C. R. Acad. Sci. Paris, Ser. I, Volume 350 (2012) no. 3–4, pp. 225-228 | DOI

[11] J. Demongeot; A. Elena; G. Weil Potential-Hamiltonian decomposition of cellular automata. Application to degeneracy of genetic code and cyclic codes III, C. R. Biologies, Volume 329 (2006), pp. 953-962

[12] J. Demongeot; C. Jezequel; S. Sené Asymptotic behavior and phase transition in regulatory networks. I Theoretical results, Neural Networks, Volume 21 (2008), pp. 962-970

[13] J. Demongeot; M. Thellier; R. Thomas Storage and recall of environmental signals in a plant: modelling by use of a differential (continuous) formulation, C. R. Biologies, Volume 329 (2006), pp. 971-978

[14] J. Demongeot; R. Thomas; M. Thellier A mathematical model for storage and recall functions in plants, C. R. Acad. Sci. Paris, Ser. III, Volume 323 (2000), pp. 93-97

[15] J. Demongeot; A. Elena; M. Noual; S. Sené Random Boolean networks and attractors of their intersecting circuits, Proceedings AINAʼ 11 & BLSMCʼ 11, IEEE Press, Piscataway, 2011, pp. 483-487

[16] J. Demongeot; H. Ben Amor; P. Gillois; M. Noual; S. Sené Robustness of regulatory networks. A generic approach with applications at different levels: physiologic, metabolic and genetic, Int. J. Mol. Sci., Volume 10 (2009), pp. 4437-4473

[17] J. Demongeot; J. Aracena; S. Ben Lamine; S. Meignen; A. Tonnelier; R. Thomas Dynamical systems and biological regulations (E. Goles; S. Martinez, eds.), Complex Systems, Kluwer, Amsterdam, 2001, pp. 105-151

Cité par Sources :

Commentaires - Politique


Ces articles pourraient vous intéresser

Robustness in biological regulatory networks II: Application to genetic threshold Boolean random regulatory networks (getBren)

Jacques Demongeot; Jules Waku

C. R. Math (2012)


Robustness in biological regulatory networks IV: Application to genetic networks controlling the cell cycle

Jacques Demongeot; Jules Waku

C. R. Math (2012)


Robustness in biological regulatory networks I: Mathematical approach

Jacques Demongeot; Jules Waku

C. R. Math (2012)