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Open AccessJournal ArticleDOI

Hierarchical Organization of Modularity in Metabolic Networks

TLDR
It is shown 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.
Abstract
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

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Journal ArticleDOI

Analysis of the Airport Network of India as a complex weighted network

TL;DR: The Airport Network of India (ANI) is found to be a small-world network characterized by a truncated power-law degree distribution and has a signature of hierarchy, indicating possible mechanism of formation of a national transportation network, which is different from that on a global scale.
Journal ArticleDOI

Epstein–Barr virus and virus human protein interaction maps

TL;DR: The authors' EBV–EBV interactome map is enriched for interactions among proteins in the same evolutionary class, and human proteins targeted by EBV proteins were enriched for highly connected or “hub” proteins and for proteins with relatively short paths to all other proteins inThe human interactome network.
Journal ArticleDOI

From correlation to causation networks: a simple approximate learning algorithm and its application to high-dimensional plant gene expression data.

TL;DR: A heuristic for the statistical learning of a high-dimensional "causal" network that not only yield sensible first order approximations of the causal structure in high- dimensional genomic data but is also computationally highly efficient.
Journal ArticleDOI

Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data

TL;DR: In this article, the authors perform analysis of a highly diverse collection of genomewide data sets, including gene expression, protein interactions, growth phenotype data, and transcription factor binding, to reveal the modular organization of the yeast system.
Proceedings ArticleDOI

Distributed community detection in delay tolerant networks

TL;DR: This work proposes and evaluates three novel distributed community detection approaches with great potential to detect both static and temporal communities and finds that with suitable configuration of the threshold values, the distributedcommunity detection can approximate their corresponding centralised methods up to 90% accuracy.
References
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Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Journal ArticleDOI

Statistical mechanics of complex networks

TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Journal ArticleDOI

Cluster analysis and display of genome-wide expression patterns

TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Journal ArticleDOI

Community structure in social and biological networks

TL;DR: This article proposes a method for detecting communities, built around the idea of using centrality indices to find community boundaries, and tests it on computer-generated and real-world graphs whose community structure is already known and finds that the method detects this known structure with high sensitivity and reliability.
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