Superfamilies of Evolved and Designed Networks

By Ron Milo, Shalev Itzkovitz, Nadav Kashtan, Reuven Levitt, S. Shen-Orr, Inbal Ayzenshtat, Michal Sheffer, Uri Alon. Science, 2004

1,383 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/87ad24efd5329046d37cd704f970323e878710ca

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Citations in the corpus

Recent advances in ecological stoichiometry: insights for population and community ecology (2005, background): “(Milo et al. 2004) to food webs can give insights into how”
Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits (2005, methodology): “One such approach is to explore local structures in network connectivity by studying the distribution of few-node connectivity patterns, or motifs [26,27].”
Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs (2004, background): “Signaling networks and developmental transcription networks show these motifs, as well as other motifs (Milo et al., 2004; Lahav et al.., 2004).”
Structured Connectivity in Cerebellar Inhibitory Networks (2014, methodology): “Because a preference for transitive connectivity has been reported in other complex networks (Holland and Leinhardt, 1970; Milo et al., 2004), we tested this hypothesis in the MLI network and therefore grouped the patterns according to their property of transitivity (Bang-Jensen and Gutin, 2008; Sup”
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training (2020, background): “aw [1]. Leskovec et al. [28] discover that a wide range of real graphs satisfy the densification and shrinking laws. Other common patterns across networks include small world [58], motif distribution [31], community organization [34], and core-periphery structure [6], validating our hypothesis at th”
Knowledge sharing and yahoo answers: everyone knows something (2008, background): “These profiles are constructed by counting the actual frequency of each triad in the QA network for that category, and then comparing that frequency against the expected frequency for randomized versions of the same network [13, 12, 21].”
Characterization of complex networks: A survey of measurements (2005, background): “linked mutual dyad. 18 It is also possible to categorize diﬀerent networks by the Z-scores of their motifs: networks that show emphasis on the same motifs can be considered as part of the same family [56]. To this purpose, the signiﬁcance proﬁle of the network is computed. The signiﬁcance proﬁle is ”
Cortical High-Density Counterstream Architectures (2013, methodology): “Only the EDR model captures the binary statistical graph properties of G29x29 on all scales (from local to global), including motif distributions (84) and graph spectral properties.”