Constrained stoichiometric network analysis

2018 ◽  
Vol 20 (15) ◽  
pp. 9910-9921 ◽  
Author(s):  
Vuk Radojković ◽  
Igor Schreiber

BZ reaction network – rate coefficients of reactions 11–14 were found by convex linear optimization at Hopf bifurcation.

2012 ◽  
Vol 66 (5) ◽  
pp. 637-646 ◽  
Author(s):  
Stevan Macesic ◽  
Zeljko Cupic ◽  
Ljiljana Kolar-Anic

Self-regulation, achieved through positive (autocatalytic) or negative (autoinhibitory) feedback is commonly encountered in natural, technological and economic systems. The dynamic behavior of such systems is often complex and cannot be easily predicted, necessitating mathematical modelling and theoretical analyses. The aim of this work is to analyze the dynamics of a minimal model system with autocatalytic and autoinhibitory steps coupled through the same species, in order to understand under which critical condition the system loses stability and passes through an Andronov-Hopf bifurcation. The analysis used was improved stoichiometric network analysis (SNA) in combination with bifurcation and sensitivity analysis.


2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Stevan R. Maćešić ◽  
Željko D. Čupić ◽  
Slavica M. Blagojević ◽  
Nataša D. Pejić ◽  
Slobodan R. Anić ◽  
...  

AbstractIn stoichiometric network analysis (SNA) the instability condition is calculated by the current rates. Recently, we have shown that in the final result the current rates can be substituted by reaction rates, which is a more appropriate value for the examination of instability from experimental point of view. Here, we elaborate the problem of whether the current rates are necessary parameters in the calculation, with the aim of obtaining the region of instability. All calculations are performed on a model for Belousov-Zhabotinsky (BZ) reaction, which has not been examined by SNA.


ChemCatChem ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2746-2746
Author(s):  
Max Leopold ◽  
Max Siebert ◽  
Alexander F. Siegle ◽  
Oliver Trapp

2003 ◽  
Vol 3 ◽  
pp. 319-341 ◽  
Author(s):  
Stefan Franzle ◽  
Bernd Markert

The biological application of stoichiometric network analysis (SNA) permits an understanding of tumour induction, carcinogenesis, and chemotherapy. Starting from the Biological System of the Elements, which provides a comprehensive treatment of the functions and distributions of chemical (trace) elements in biology, an attempt is made to interrelate the essential feature of biology and — regrettably — of tumour genesis by superimposing SNA reasoning on common features of all crucial biological processes. For this purpose, aspects, effects and drawbacks of autocatalysis (identical reproduction which can occur either under control or without control [in tumours]) are linked with the known facts about element distributions in living beings and about interference of metals with tumours (in terms of both chemotherapy and carcinogenesis). The essential role of autocatalysis in biology and the drawbacks of either controlled or spontaneous cell division can be used to understand crucial aspects of carcinogenesis and chemotherapy because SNA describes and predicts effects of autocatalysis, including phase effects that may be due to some kind of intervention. The SNA-based classifications of autocatalytic networks in cell biology are outlined here to identify new approaches to chemotherapy.


MRS Advances ◽  
2016 ◽  
Vol 1 (24) ◽  
pp. 1767-1772 ◽  
Author(s):  
Qian Yang ◽  
Carlos A. Sing-Long ◽  
Evan J. Reed

ABSTRACTKinetic Monte Carlo (KMC) methods have been a successful technique for accelerating time scales and increasing system sizes beyond those achievable with fully atomistic simulations. However, a requirement for its success is a priori knowledge of all relevant reaction pathways and their rate coefficients. This can be difficult for systems with complex chemistry, such as shock-compressed materials at high temperatures and pressures or phenolic spacecraft heat shields undergoing pyrolysis, which can consist of hundreds of molecular species and thousands of distinct reactions. In this work, we develop a method for first estimating a KMC model composed of elementary reactions and rate coefficients by using large datasets derived from a few molecular dynamics (MD) simulations of shock compressed liquid methane, and then using L1 regularization to reduce the estimated chemical reaction network. We find that the full network of 2613 reactions can be reduced by 89% while incurring approximately 9% error in the dominant species (CH4) population. We find that the degree of sparsity achievable decreases when similar accuracy is required for additional populations of species.


2017 ◽  
Vol 19 (14) ◽  
pp. 3263-3271 ◽  
Author(s):  
Toni Pfennig ◽  
Robert L. Johnson ◽  
Brent H. Shanks

Diels–Alder cycloaddition of biomass-derived 2-pyrone coumalic acid (CMA) with propylene provides an alternative pathway to produce toluic acid (TA), a precursor to terephthalic acid (TPA) which is a key component in the manufacture of polyethylene terephthalate (PET).


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