Hierarchical Organization of Modularity in Metabolic Networks

By E. Ravasz, A. Somera, D. A. Mongru, Zoltn Oltvai, Albert-László Barabási. Science, 2002

4,156 citations recorded by the source corpus.

Spatially or chemically isolated functional modules composed of several cellular components and carrying discrete functions are considered fundamental building blocks of cellular organization, but their presence in highly integrated biochemical networks lacks quantitative support. Here, we show that the metabolic networks of 43 distinct organisms are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units, with their number and degree of clustering following a power law. Within Escherichia coli, the uncovered hierarchical modularity closely overlaps with known metabolic functions. The identified network architecture may be generic to system-level cellular organization.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a33bbacc55b69adf894bbb1b423b9b4c5b031ae0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

Origins of fractality in the growth of complex networks (2005, background): “(a) Resulting topology predicted by the minimal model for e = 0.8, n = 5, a = 1.4, s = 3 and m = 2.”
Recommender Systems (2012, methodology): “By considering degrees of the two target nodes, six variations of CN were derived: Salton Index [140], Jaccard Index [141], Sørensen Index [142], Hub Promoted Index (HPI) [143], Hub Depressed Index (HDI) and Leicht–Holme–Newman Index (LHN1 6 ) [144].”
Functional topology in a network of protein interactions (2004, background): “, 2002), which are hierarchically organized into modules (Ravasz et al., 2002).”
Gene co-expression network topology provides a framework for molecular characterization of cellular state (2004, background): “they exhibit power-law node-degree distributions (Jeong et al., 2001; Ravasz et al., 2002; Snel et al., 2002; Williams et al., 2002).”
Kronecker Graphs: An Approach to Modeling Networks (2008, background): “In fact, several researchers have argued that real networks are hierarchically organized (Ravasz et al., 2002; Ravasz and Barabási, 2003) and algorithms to extract the network hierarchical structure have also been developed (Sales-Pardo et al., 2007; Clauset et al., 2008).”
A Comprehensive Survey on Community Detection With Deep Learning (2021, background): “In metabolic networks [27], [28] and protein-protein interaction (PPI) networks [29], community detection reveals the complexities of metabolisms and identiﬁes proteins with similar biological functions.”
Introduction to systems biology. (2007, background): “Most noticeably are small world organization [57, 58], modularity [59, 60], motifs [61–63], fl ux balance analysis, extreme pathway and elementary mode analysis [6, 64–67].”
Microbial Co-occurrence Relationships in the Human Microbiome (2012, background): “, with only sparse local multi-organism clusters. Since these data only describe phylotypes at approximately the genus level, it remains to be seen whether a greater degree of locally clustered functional associations emerges among Operational Taxonomic Units (OTUs), species, or strains within these”
Community detection in graphs (2009, methodology): “Hierarchical organization is a common feature of many real networks, where it is revealed by a peculiar scaling of the clustering coefficient for vertices having the same degree k, when plotted as a function of k [108,109].”
Graph theory and networks in Biology. (2006, background): “The hypothesis underpinning these so-called Duplication-Divergence (DD) models is that gene and protein networks evolve through the occasional copying of individual genes/proteins, followed by subsequent mutations.”