The small world inside large metabolic networks

By Andreas Wagner, David A. Fell. Proceedings of the Royal Society of London. Series B: Biological Sciences, 2000

1,053 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6e970198adf717b6e7dc2dcb406ff14535b53e16

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Citations in the corpus

Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “scale-free, few hubs concentrate a high number of connectio ns [346].”
Genomic analysis of regulatory network dynamics reveals large topological changes (2004, background): “The view from recent studies is that these statistics are remarkably constant across many biological networks (including regulatory systems”
Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs (2004, methodology): “It would be interesting to apply network motif analysis, assisted by tools such as the sampling method, to metabolic (Ouzounis and Karp, 2000; Wagner and Fell, 2001), signaling, immunological and other biological networks.”
A human functional protein interaction network and its application to cancer data analysis (2010, background): “The FI network shows scale-free properties (data not shown) as do other biological networks [65-68].”
Complexity and fragility in ecological networks (2000, background): “These networks go from technological ones (Watts and Strogatz, 1998; Albert et al., 1999), to neural (Watts and Strogatz 1998; Amaral et al., 2000) or metabolic networks (Jeong et al 2000; Wagner and Fell, 2000).”
Transcriptional Regulatory Networks in Saccharomyces cerevisiae (2009, background): “Most biological networks are thought to have a small diameter because it minimizes transition times and is thus more efficient and responsive through enhanced signal-propagation speed [12,13].”
Random graphs with arbitrary degree distributions and their applications. (2000, background): “[17] A.”
Subnetwork hierarchies of biochemical pathways (2002, background): “The general picture of the metabolic networks arising from our study is that of a few core-clusters centred around the most highly connected substances enclosed by other substances in outer shells, and a few other well-defined subnetworks.”
Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. (2005, background): “…is based on the frequency with which a node lies on the shortest path between all other nodes; proteins with high betweenness control the flow of information across a network and, thus, can be important for minimizing response times within a cell (Jeong et al. 2000; Wagner and Fell 2001).”
Analysis of Biological Networks (2008, background): “Though there is increasing interest in the analysis of dynamic aspects of complex networks, the precise relationship between structure and function of complex networks is still largely unclear [30,37,55,63,68].”