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A Toy Model of Chemical Reaction Networks - TBI - Universität Wien

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52 CHAPTER 6. COMPUTATIONAL RESULTS<br />

from a mixture <strong>of</strong> formaldehyde and glycol. The first condensation step<br />

yielding glycol from formaldehyde is assumed implicitly. The rewrite rule<br />

used is a variant <strong>of</strong> the one described in fig. 4.3. In order to account for<br />

cyclization, and so to reduce the network, carbon chains with more than four<br />

members, or two chains with four members were not permitted to further<br />

undergo aldol condensation. Furthermore, although more than 40 different<br />

sugars have been identified in the experimental reaction mixture [24], condensation<br />

was restricted to enoles with a primary acid hydrogen. Due to<br />

this model reduction, the algorithm converged after only two iterations. The<br />

<strong>Toy</strong> <strong>Model</strong> could be made more accurate by a Monte Carlo CRN generation.<br />

It would have the same limits implicitly because unimolecular cyclization is<br />

by far faster than bimolecular aldol condensation. This is equivalent to the<br />

systematic model reduction described by [43].<br />

6.3 Graph-theoretic properties<br />

For assessing 〈L〉 and 〈C〉, we need to compare them to the results for random<br />

Erdös-Renyi graphs:<br />

〈L rand 〉 ≈ ln n<br />

ln 〈k〉<br />

〈k〉<br />

〈C rand 〉 =<br />

(n − 1)<br />

Tab. 6.1 compares the network characteristics <strong>of</strong> the Diels-Alder, the<br />

Formose, and the E. coli metabolic network. They are all sparse graphs, i.e.<br />

they have much fewer edges than complete graphs, reflected by m ≪ n(n−1)<br />

2<br />

or 〈k〉 ≪ n. Sparse networks are very common, ranging from the network<br />

<strong>of</strong> acquaintances to a neural network. In both cases, there are only few<br />

connections at each node.<br />

The small-world phenomenon [118, 119] is also widespread, and applies<br />

for instance to the network <strong>of</strong> acquaintances. In the latter example, it describes<br />

the fact that every person is acquainted to another over “six degrees<br />

<strong>of</strong> separation”, in average. More generally, it means that the average shortest<br />

path between two nodes in a network is small. An important application is<br />

the propagation <strong>of</strong> diseases, where the small-world property leads to a rapid<br />

spread. From the networks <strong>of</strong> tab. 6.1, only Diels-Alder and E. coli fulfill the<br />

conditions 〈C〉 ≫ 〈C rand 〉 and 〈L〉 ≤ 〈L rand 〉 and thus are strictly small-world<br />

networks. The Formose reaction network includes many non-reactive species<br />

with respect to keto-enol condensation, which leads to small cliquishness and<br />

longer paths.

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