Complexity and robustness in hypernetwork models of metabolism

Pearcy, N., Chuzhanova, N. ORCID: 0000-0002-4655-3618 and Crofts, J.J. ORCID: 0000-0001-7751-9984, 2016. Complexity and robustness in hypernetwork models of metabolism. Journal of Theoretical Biology, 406, pp. 99-104. ISSN 0022-5193

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Metabolic reaction data is commonly modelled using a complex network approach, whereby nodes represent the chemical species present within the organism of interest, and connections are formed between those nodes participating in the same chemical reaction. Unfortunately, such an approach provides an inadequate description of the metabolic process in general, as a typical chemical reaction will involve more than two nodes, thus risking over-simplification of the the system of interest in a potentially significant way. In this paper, we employ a complex hypernetwork formalism to investigate the robustness of bacterial metabolic hypernetworks by extending the concept of a percolation process to hypernetworks. Importantly, this provides a novel method for determining the robustness of these systems and thus for quantifying their resilience to random attacks/errors. Moreover, we performed a site percolation analysis on a large cohort of bacterial metabolic networks and found that hypernetworks that evolved in more variable enviro nments displayed increased levels of robustness and topological complexity.

Item Type: Journal article
Publication Title: Journal of Theoretical Biology
Creators: Pearcy, N., Chuzhanova, N. and Crofts, J.J.
Publisher: Elsevier
Date: 7 October 2016
Volume: 406
ISSN: 0022-5193
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 27 Jul 2016 07:55
Last Modified: 25 Jun 2017 03:00

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