Random Network Based Dynamic Analysis for Biochemical Reaction System

2012 ◽  
Vol 10 (1) ◽  
pp. 554-558
Author(s):  
Shu-Qiang Wang ◽  
Han-Xiong Li
Keyword(s):  
Dynamic Analysis ◽  
Random Network ◽  
Reaction System ◽  
Biochemical Reaction

MICROSCOPIC SELF-ORGANIZATION IN NETWORKS AND REGULAR LATTICE

2002 ◽  
Vol 16 (25) ◽  
pp. 923-935
Author(s):  
QI OUYANG ◽  
KAI SUN ◽  
HONGLI WANG
Keyword(s):  
Correlation Length ◽  
Random Network ◽  
Reaction System ◽  
Small World ◽  
Self Organization ◽  
Fast Diffusion ◽  
Small World Network ◽  
Regular Lattice ◽  
Numerical Studies ◽  
Regular Network

We report our numerical studies on the microscopic self-organizations of a reaction system in three types of networks: a regular network, a small-world network, and a random network as well as on a regular lattice. Our simulation results show that the topology of the network has an important effect on the communication among reaction molecules, and plays an important role in microscopic self-organization. The correlation length among reacting molecules in a random or a small-world network is much shorter compared with that in the regular network. As a result, it is much easier to obtain a microscopic self-organization in a small-world or a random network. A phase transition from a stochastic state to a synchronized state was observed when the randomness of a small-world network was increased. We also demonstrate that good synchronization activities of enzymatic turnover cycles can be developed on a regular lattice when the correlation length created by the fast diffusion of regulatory particles is large enough.

DYNAMIC ANALYSIS AND CONTROL OF CHEMICAL AND BIOCHEMICAL REACTION NETWORKS

2006 ◽  
Vol 39 (2) ◽  
pp. 165-170 ◽  
Author(s):  
Irene Otero-Muras ◽  
Gábor Szederkényi ◽  
Antonio A. Alonso ◽  
Katalin M. Hangos
Keyword(s):  
Dynamic Analysis ◽  
Biochemical Reaction ◽  
Reaction Networks ◽  
Biochemical Reaction Networks ◽  
And Control

scholarly journals Dynamic analysis and control of biochemical reaction networks

2008 ◽  
Vol 79 (4) ◽  
pp. 999-1009 ◽  
Author(s):  
Irene Otero-Muras ◽  
Gábor Szederkényi ◽  
Katalin M. Hangos ◽  
Antonio A. Alonso
Keyword(s):  
Dynamic Analysis ◽  
Biochemical Reaction ◽  
Reaction Networks ◽  
Biochemical Reaction Networks ◽  
And Control

Preliminary Dynamics Analysis for Synthesis of Polyamide Polyamine Compounds (PPC)

2011 ◽  
Vol 396-398 ◽  
pp. 904-907
Author(s):  
Jian Chen ◽  
Hong Xiang Zhu ◽  
Li Jun Wang ◽  
Nan Nan Xia ◽  
Shuang Fei Wang
Keyword(s):  
Kinetic Equation ◽  
Dynamic Analysis ◽  
Adipic Acid ◽  
Reaction System ◽  
Dynamics Analysis

In this paper, preliminary dynamics analysis of synthesis of polyamide polyamine compounds was deduced by kinetic equation. The dynamic analysis shows that the reaction of polyethylene polyamines with adipic acid belongs to typical three reactions. In the kinetic equation, the concentration of carboxyl failed to reflect the ability of provided protons that reaction system to amine.

Fabrication of a pen-shaped portable biochemical reaction system based on magnetic bead manipulation

2011 ◽  
Vol 21 (6) ◽  
pp. 067006 ◽  
Author(s):  
Mitsuhiro Shikida ◽  
Noriyuki Inagaki ◽  
Mina Okochi ◽  
Hiroyuki Honda ◽  
Kazuo Sato
Keyword(s):  
Reaction System ◽  
Magnetic Bead ◽  
Biochemical Reaction

scholarly journals Dynamic analysis of biochemical network using complex network method

2015 ◽  
Vol 19 (4) ◽  
pp. 1249-1253 ◽  
Author(s):  
Shuqiang Wang ◽  
Yanyan Shen ◽  
Jinxing Hu ◽  
Ning Li ◽  
Dewei Zeng
Keyword(s):  
Complex Network ◽  
Reaction System ◽  
Reaction Network ◽  
Reaction Model ◽  
Mass Action ◽  
Biochemical Reaction ◽  
Biochemical Network ◽  
Initial State ◽  
Complex Network Theory ◽  
Linear Differential

In this study, the stochastic biochemical reaction model is proposed based on the law of mass action and complex network theory. The dynamics of biochemical reaction system is presented as a set of non-linear differential equations and analyzed at the molecular-scale. Given the initial state and the evolution rules of the biochemical reaction system, the system can achieve homeostasis. Compared with random graph, the biochemical reaction network has larger information capacity and is more efficient in information transmission. This is consistent with theory of evolution.

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