Model validation of simple-graph representations of metabolism
2009 (English)In: Journal of the Royal Society Interface, ISSN 1742-5662, E-ISSN 1742-5689, Vol. 6, no 40, 1027-1034 p.Article in journal (Refereed) Published
The large-scale properties of chemical reaction systems, such as metabolism, can be studied with graph-based methods. To do this, one needs to reduce the information, lists of chemical reactions, available in databases. Even for the simplest type of graph representation, this reduction can be done in several ways. We investigate different simple network representations by testing how well they encode information about one biologically important network structure-network modularity (the propensity for edges to be clustered into dense groups that are sparsely connected between each other). To achieve this goal, we design a model of reaction systems where network modularity can be controlled and measure how well the reduction to simple graphs captures the modular structure of the model reaction system. We find that the network types that best capture the modular structure of the reaction system are substrate-product networks (where substrates are linked to products of a reaction) and substance networks (with edges between all substances participating in a reaction). Furthermore, we argue that the proposed model for reaction systems with tunable clustering is a general framework for studies of how reaction systems are affected by modularity. To this end, we investigate statistical properties of the model and find, among other things, that it recreates correlations between degree and mass of the molecules.
Place, publisher, year, edition, pages
2009. Vol. 6, no 40, 1027-1034 p.
chemical networks, complex networks, chemical reaction systems, statistical graph methods
Social Sciences Interdisciplinary
IdentifiersURN: urn:nbn:se:kth:diva-24690DOI: 10.1098/rsif.2008.0489ISI: 000270143300006ScopusID: 2-s2.0-70349759581OAI: oai:DiVA.org:kth-24690DiVA: diva2:352821
QC 201009222010-09-222010-09-222010-09-22Bibliographically approved