Sufficient and necessary conditions for Lyapunov stability of genetic networks with SUM regulatory logic.

Guopeng Zhou, Jinhua Huang, Fengxia Tian, Xiaoxin Liao

Abstract read

In one paragraph

Article in Cognitive neurodynamics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 citing paper in PubMed.

Bacterial gene regulatory neural network as a biocomputing library of mathematical solvers.NPJ systems biology and applications · 2026
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Authors and funding

4 authors.

Guopeng ZhouInstitute of Engineering and Technology, Hubei University of Science and Technology, Xianning, 437100 China.

Jinhua HuangDepartment of Electric and Electronic Engineering, Wuhan Institute of Shipbuilding Technology, Wuhan, 430050 China.

Fengxia TianInstitute of Engineering and Technology, Hubei University of Science and Technology, Xianning, 437100 China.

Xiaoxin LiaoInstitute of Engineering and Technology, Hubei University of Science and Technology, Xianning, 437100 China ; College of Automation, Huazhong University of Science and Technology, Wuhan, 430074 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, a nonlinear model for genetic regulator networks (GRNs) with SUM regulatory logic is presented. Four sufficient and necessary conditions of global asymptotical stability and global exponential stability for the equilibrium point of the GRNs are proposed, respectively. Specifically, three weak sufficient conditions and corresponding corollaries are derived by using comparing theorem and Dini derivative method. Then, a famous GRN model is used as the example to illustrate the effectiveness of our theoretical results. Comparing to the results in the previous literature, some novel ideas, study methods and interesting results are explored.

Indexed as

Asymptotical stabilityComparing theoremDini derivativeExponential stabilityGenetic regulator networks

Identifiers

PMID26157517

DOI10.1007/s11571-015-9341-5

PMCPMC4491336

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