A study into the structure and evolution of large metabolic networks

The entry of science into the post genomic era has created a magnitude of available data for metabolic networks. Full metabolic networks are yet too complex to model kinetically and a step back has to be taken to compare metabolisms from different organisms. In order to reduce the complexity of the problem, kinetics of the reactions is removed leaving only the reaction and metabolic architecture. The structure of chemical reactions is particularly intriguing with a single reaction connecting various reactants with numerous products. Metabolic networks were converted into a series of mathematical graphs and the topographical properties were probed. Using this information, various different modes of network construction were developed to design and evolve networks with specific properties. It was found that a scale free architecture that mimics a metabolic network could be created by optimising topology towards higher connectivity. The only true representation of connectivity is using a summation of all paths between metabolites in a network. Molecular structure of metabolites can be depicted as a graph and reactions modelled as graph transformations. Using this as an artificial chemistry, novel ways of creating and filtering chemical reaction networks were developed.