Global stability analysis of fractional-order gene regulatory networks with time delay

2019 ◽  
Vol 12 (06) ◽  
pp. 1950067 ◽  
Author(s):  
Zhaohua Wu ◽  
Zhiming Wang ◽  
Tiejun Zhou
Keyword(s):  
Time Delay ◽  
Fractional Order ◽  
Gene Regulatory Networks ◽  
Existence And Uniqueness ◽  
Regulatory Networks ◽  
Lyapunov Method ◽  
Regulation Mechanism ◽  
Global Stability Analysis ◽  
Gene Regulatory ◽  
The Stability

Fractional-order gene regulatory networks with time delay (DFGRNs) have proven that they are more suitable to model gene regulation mechanism than integer-order. In this paper, a novel DFGRN is proposed. The existence and uniqueness of the equilibrium point for the DFGRN are proved under certain conditions. On this basis, the conditions on the global asymptotic stability are established by using the Lyapunov method and comparison theorem for the DFGRN, and the stability conditions are dependent on the fractional-order [Formula: see text]. Finally, numerical simulations show that the obtained results are reasonable.

scholarly journals Global uniform asymptotical stability for fractional-order gene regulatory networks with time-varying delays and structured uncertainties

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Zhaohua Wu ◽  
Zhiming Wang ◽  
Tiejun Zhou
Keyword(s):  
Fractional Order ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Contraction Mapping ◽  
Contraction Mapping Principle ◽  
Time Varying ◽  
The Novel ◽  
Razumikhin Technique ◽  
Gene Regulatory ◽  
The Stability

AbstractIn this paper, we investigate a class of fractional-order gene regulatory networks with time-varying delays and structured uncertainties (UDFGRNs). First, we deduce the existence and uniqueness of the equilibrium for the UDFGRNs by using the contraction mapping principle. Next, we derive a novel global uniform asymptotic stability criterion of the UDFGRNs by using a Lyapunov function and the Razumikhin technique, and the conditions relating to the criterion depend on the fractional order of the UDFGRNs. Finally, we provide two numerical simulation examples to demonstrate the correctness and usefulness of the novel stability conditions. One of the most interesting findings is that the structured uncertainties indeed have an impact on the stability of the system.

scholarly journals Gene regulatory network stabilized by pervasive weak repressions: microRNA functions revealed by the May–Wigner theory

2019 ◽  
Vol 6 (6) ◽  
pp. 1176-1188 ◽  
Author(s):  
Yuxin Chen ◽  
Yang Shen ◽  
Pei Lin ◽  
Ding Tong ◽  
Yixin Zhao ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Biological Networks ◽  
Regulatory Network ◽  
Mammalian Cells ◽  
Regulatory Networks ◽  
Yeast Cells ◽  
Gene Products ◽  
Mathematical Solution ◽  
Gene Regulatory ◽  
The Stability

Abstract Food web and gene regulatory networks (GRNs) are large biological networks, both of which can be analyzed using the May–Wigner theory. According to the theory, networks as large as mammalian GRNs would require dedicated gene products for stabilization. We propose that microRNAs (miRNAs) are those products. More than 30% of genes are repressed by miRNAs, but most repressions are too weak to have a phenotypic consequence. The theory shows that (i) weak repressions cumulatively enhance the stability of GRNs, and (ii) broad and weak repressions confer greater stability than a few strong ones. Hence, the diffuse actions of miRNAs in mammalian cells appear to function mainly in stabilizing GRNs. The postulated link between mRNA repression and GRN stability can be seen in a different light in yeast, which do not have miRNAs. Yeast cells rely on non-specific RNA nucleases to strongly degrade mRNAs for GRN stability. The strategy is suited to GRNs of small and rapidly dividing yeast cells, but not the larger mammalian cells. In conclusion, the May–Wigner theory, supplanting the analysis of small motifs, provides a mathematical solution to GRN stability, thus linking miRNAs explicitly to ‘developmental canalization’.

scholarly journals Using GeneReg to construct time delay gene regulatory networks

2010 ◽  
Vol 3 (1) ◽  
Author(s):  
Tao Huang ◽  
Lei Liu ◽  
Ziliang Qian ◽  
Kang Tu ◽  
Yixue Li ◽  
...  
Keyword(s):  
Time Delay ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Gene Regulatory

scholarly journals The Dynamics of Canalizing Boolean Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Elijah Paul ◽  
Gleb Pogudin ◽  
William Qin ◽  
Reinhard Laubenbacher
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Boolean Network ◽  
Boolean Networks ◽  
Molecular Networks ◽  
Biological Applications ◽  
Expected Number ◽  
Modeling Framework ◽  
Gene Regulatory ◽  
The Stability

Boolean networks are a popular modeling framework in computational biology to capture the dynamics of molecular networks, such as gene regulatory networks. It has been observed that many published models of such networks are defined by regulatory rules driving the dynamics that have certain so-called canalizing properties. In this paper, we investigate the dynamics of a random Boolean network with such properties using analytical methods and simulations. From our simulations, we observe that Boolean networks with higher canalizing depth have generally fewer attractors, the attractors are smaller, and the basins are larger, with implications for the stability and robustness of the models. These properties are relevant to many biological applications. Moreover, our results show that, from the standpoint of the attractor structure, high canalizing depth, compared to relatively small positive canalizing depth, has a very modest impact on dynamics. Motivated by these observations, we conduct mathematical study of the attractor structure of a random Boolean network of canalizing depth one (i.e., the smallest positive depth). For every positive integer ℓ, we give an explicit formula for the limit of the expected number of attractors of length ℓ in an n-state random Boolean network as n goes to infinity.

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