scholarly journals Critical transitions in a model of a genetic regulatory system

2014 ◽  
Vol 11 (4) ◽  
pp. 723-740 ◽  
Author(s):  
Jesse Berwald ◽  
◽  
Marian Gidea ◽  
Keyword(s):  
Regulatory System ◽  
Critical Transitions ◽  
Genetic Regulatory System

scholarly journals Likelihood for transcriptions in a genetic regulatory system under asymmetric stable Lévy noise

2018 ◽  
Vol 28 (1) ◽  
pp. 013121 ◽  
Author(s):  
Hui Wang ◽  
Xiujun Cheng ◽  
Jinqiao Duan ◽  
Jürgen Kurths ◽  
Xiaofan Li
Keyword(s):  
Regulatory System ◽  
Lévy Noise ◽  
Genetic Regulatory System ◽  
Levy Noise

Synergy of feedback mechanisms in gene regulation systems with promoter and repressor transcription factors

Open Physics ◽  
2008 ◽  
Vol 6 (1) ◽  
Author(s):  
Fedor Šrobár
Keyword(s):  
Gene Regulation ◽  
Transcription Factors ◽  
Negative Feedback ◽  
Regulatory System ◽  
Exact Formulation ◽  
Feedback Mechanisms ◽  
Repressor Proteins ◽  
Positive And Negative Feedback ◽  
Responsive Element ◽  
Genetic Regulatory System

AbstractPresence of feedback mechanisms, both positive and negative, in the gene regulation systems is generally appreciated. The present study proposes a diagrammatic representation of these phenomena that affords their exact formulation and reveals some new facts. Topology of feedback relationships is defined by diagram configuration and quantitative evaluation is afforded by analytical apparatus coming with the diagrams. In particular, criterion for occurrence of bistability and synergy of positive and negative feedback are described in exact manner using the concept of transmission functions associated with diagram edges. The approach is demonstrated on genetic regulatory system comprising two genes whose transcription is controlled by activator and repressor proteins mutually competing for binding to the same responsive element of the DNA.

MODELING GENETIC REGULATORY NETWORKS: CONTINUOUS OR DISCRETE?

2006 ◽  
Vol 14 (02) ◽  
pp. 219-229 ◽  
Author(s):  
IVAN IVANOV ◽  
EDWARD R. DOUGHERTY
Keyword(s):  
Regulatory Networks ◽  
Dynamical Behavior ◽  
Regulatory System ◽  
Genetic Regulatory Networks ◽  
Discrete Models ◽  
Fine Scale ◽  
Differential Equation Models ◽  
Scale Models ◽  
Genetic Regulatory System

Selecting an appropriate mathematical model to describe the dynamical behavior of a genetic regulatory network plays an important part in discovering gene regulatory mechanisms. Whereas fine-scale models can in principle provide a very accurate description of the real genetic regulatory system, one must be aware of the availability and quality of the data used to infer such models. Consequently, pragmatic considerations motivate the selection of a model possessing minimal complexity among those capable of capturing the level of real gene regulation being studied, particularly in relation to the prediction capability of the model. This paper compares fine-scale stochastic-differential-equation models with coarse-scale discrete models in the context of currently available data and with respect to their description of switch-like behavior among specific groups of genes.

scholarly journals An information-theoretic model suggesting genetic regulatory system degradation under climate change

Physics Open ◽  
2021 ◽  
Vol 6 ◽  
pp. 100062
Author(s):  
Katsumi Sakata ◽  
Toshiyuki Saito ◽  
Hajime Ohyanagi ◽  
Ramesh Katam ◽  
Setsuko Komatsu
Keyword(s):  
Climate Change ◽  
Regulatory System ◽  
Theoretic Model ◽  
Information Theoretic ◽  
Genetic Regulatory System

scholarly journals Time-Based Switching Control of Genetic Regulatory Networks: Toward Sequential Drug Intake for Cancer Therapy

2017 ◽  
Vol 16 ◽  
pp. 117693511770688 ◽  
Author(s):  
Wasiu Opeyemi Oduola ◽  
Xiangfang Li ◽  
Chang Duan ◽  
Lijun Qian ◽  
Fen Wu ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Regulatory System ◽  
Standard Of Care ◽  
Genetic Regulatory Networks ◽  
Switching Function ◽  
System Control ◽  
Regulatory Systems ◽  
Survival Pathways ◽  
The Stability ◽  
Genetic Regulatory System

As cancer growth and development typically involves multiple genes and pathways, combination therapy has been touted as the standard of care in the treatment of cancer. However, drug toxicity becomes a major concern whenever a patient takes 2 or more drugs simultaneously at the maximum tolerable dosage. A potential solution would be administering the drugs in a sequential or alternating manner rather than concurrently. This study therefore examines the feasibility of such an approach from a switched system control perspective. Particularly, we study how genetic regulatory systems respond to sequential (switched) drug inputs using the time-based switching mechanism. The design of the time-driven drug switching function guarantees the stability of the genetic regulatory system and the repression of the diseased genes. Simulation results using proof-of-concept models and the proliferation and survival pathways with sequential drug inputs show the effectiveness of the proposed approach.

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