From systems biology to systems chemistry: metabolomic procedures enable insight into complex chemical reaction networks in water

RSC Advances ◽  
2014 ◽  
Vol 4 (32) ◽  
pp. 16777 ◽  
Author(s):  
Michaël Méret ◽  
Daniel Kopetzki ◽  
Thomas Degenkolbe ◽  
Sabrina Kleessen ◽  
Zoran Nikoloski ◽  
...  
Keyword(s):  
Systems Biology ◽  
Chemical Reaction ◽  
Chemical Reaction Networks ◽  
Reaction Networks ◽  
Complex Chemical ◽  
Complex Chemical Reaction ◽  
Systems Chemistry ◽  
Insight Into

scholarly journals Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry

2014 ◽  
Vol 10 (3) ◽  
pp. 897-907 ◽  
Author(s):  
Dmitrij Rappoport ◽  
Cooper J. Galvin ◽  
Dmitry Yu. Zubarev ◽  
Alán Aspuru-Guzik
Keyword(s):  
Quantum Chemistry ◽  
Chemical Reaction ◽  
Chemical Reaction Networks ◽  
Reaction Networks ◽  
Complex Chemical ◽  
Complex Chemical Reaction

A Synthon Approach to Artificial Chemistry

2009 ◽  
Vol 15 (1) ◽  
pp. 89-103 ◽  
Author(s):  
Tom Lenaerts ◽  
Hugues Bersini
Keyword(s):  
Chemical Reaction ◽  
Reaction Network ◽  
Logical Structure ◽  
Chemical Reaction Networks ◽  
The Other ◽  
Reaction Networks ◽  
Complex Chemical ◽  
Topological Evolution ◽  
The One ◽  
Insight Into

A coevolutionary model is discussed that incorporates the logical structure of constitutional chemistry and its kinetics on the one hand and the topological evolution of the chemical reaction network on the other hand. The motivation for designing this model is twofold. First, experiments that are to provide insight into chemical problems should be expressed in a syntax that remains as close as possible to real chemistry. Second, the study of physical properties of the complex chemical reaction networks requires growing models that incorporate features realistic from a biochemical perspective. In this article the theory and algorithms underlying the coevolutionary model are explained, and two illustrative examples are provided. These examples show that one needs to be careful in making general claims concerning the structure of chemical reaction networks.

scholarly journals Grip on complexity in chemical reaction networks

2017 ◽  
Vol 13 ◽  
pp. 1486-1497 ◽  
Author(s):  
Albert S Y Wong ◽  
Wilhelm T S Huck
Keyword(s):  
Complex Networks ◽  
Chemical Reaction ◽  
Biological Networks ◽  
Chemical Reaction Networks ◽  
Living Systems ◽  
Reaction Networks ◽  
Natural Systems ◽  
Systems Chemistry ◽  
Single Chemical ◽  
And Control

A new discipline of “systems chemistry” is emerging, which aims to capture the complexity observed in natural systems within a synthetic chemical framework. Living systems rely on complex networks of chemical reactions to control the concentration of molecules in space and time. Despite the enormous complexity in biological networks, it is possible to identify network motifs that lead to functional outputs such as bistability or oscillations. To truly understand how living systems function, we need a complete understanding of how chemical reaction networks (CRNs) create function. We propose the development of a bottom-up approach to design and construct CRNs where we can follow the influence of single chemical entities on the properties of the network as a whole. Ultimately, this approach should allow us to not only understand such complex networks but also to guide and control their behavior.

scholarly journals Early warning signals in chemical reaction networks

2020 ◽  
Vol 56 (26) ◽  
pp. 3725-3728
Author(s):  
Oliver R. Maguire ◽  
Albert S. Y. Wong ◽  
Jan Harm Westerdiep ◽  
Wilhelm T. S. Huck
Keyword(s):  
Complex Systems ◽  
Chemical Reaction ◽  
Early Warning ◽  
Reaction Network ◽  
Chemical Reaction Networks ◽  
Chemical Reaction Network ◽  
Reaction Networks ◽  
Warning Signals ◽  
Early Warning Signals ◽  
Complex Chemical

Many natural and man-made complex systems display early warning signals when close to an abrupt shift in behaviour. Here we show that such early warning signals appear in a complex chemical reaction network.

scholarly journals Insights into the relation between noise and biological complexity

2017 ◽  
Author(s):  
Fabrizio Pucci ◽  
Marianne Rooman
Keyword(s):  
Steady State ◽  
Systems Biology ◽  
Chemical Reaction ◽  
Intrinsic Noise ◽  
Chemical Reaction Networks ◽  
Reaction Networks ◽  
Global Level ◽  
Biological Complexity ◽  
Lower Complexity

Understanding under which conditions the increase of systems complexity is evolutionary advantageous, and how this trend is related to the modulation of the intrinsic noise, are fascinating issues of utmost importance for synthetic and systems biology. To get insights into these matters, we analyzed chemical reaction networks with different topologies and degrees of complexity, interacting or not with the environment. We showed that the global level of fluctuations at the steady state, as measured by the sum of the Fano factors of the number of molecules of all species, is directly related to the topology of the network. For systems with zero deficiency, this sum is constant and equal to the rank of the network. For higher deficiencies, we observed an increase or decrease of the fluctuation levels according to the values of the reaction fluxes that link internal species, multiplied by the associated stoichiometry. We showed that the noise is reduced when the fluxes all flow towards the species of higher complexity, whereas it is amplified when the fluxes are directed towards lower complexity species.PACS numbers: 02.50.Ey, 05.10.Gg, 05.40.Ca, 87.18.-h

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