PEARCY, N., CROFTS, J.J. and CHUZHANOVA, N., 2014. Hypergraph models of metabolism. International Journal of Biological, Veterinary, Agricultural and Food Engineering, 8 (8), pp. 752-756.
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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterise a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.
|Item Type:||Journal article|
|Publication Title:||International Journal of Biological, Veterinary, Agricultural and Food Engineering|
|Creators:||Pearcy, N., Crofts, J.J. and Chuzhanova, N.|
|Publisher:||World Academy of Science, Engineering and Technology|
|Rights:||© 2014 World Academy of Science, Engineering and Technology|
|Divisions:||Schools > School of Science and Technology|
|Depositing User:||EPrints Services|
|Date Added:||09 Oct 2015 10:10|
|Last Modified:||19 Oct 2015 14:28|
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