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398
The structure and function of complex networks
- SIAM REVIEW
, 2003
"... Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, ..."
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Cited by 2600 (7 self)
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Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
The spread of behavior in an online social network experiment,”
- Science
, 2010
"... How do social networks affect the spread of behavior? A popular hypothesis states that networks with many clustered ties and a high degree of separation will be less effective for behavioral diffusion than networks in which locally redundant ties are rewired to provide shortcuts across the social s ..."
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Cited by 214 (4 self)
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How do social networks affect the spread of behavior? A popular hypothesis states that networks with many clustered ties and a high degree of separation will be less effective for behavioral diffusion than networks in which locally redundant ties are rewired to provide shortcuts across the social space. A competing hypothesis argues that when behaviors require social reinforcement, a network with more clustering may be more advantageous, even if the network as a whole has a larger diameter. I investigated the effects of network structure on diffusion by studying the spread of health behavior through artificially structured online communities. Individual adoption was much more likely when participants received social reinforcement from multiple neighbors in the social network. The behavior spread farther and faster across clustered-lattice networks than across corresponding random networks.
Scale-free networks in cell biology
- JOURNAL OF CELL SCIENCE
"... A cell’s behavior is a consequence of the complex interactions between its numerous constituents, such as DNA, RNA, proteins and small molecules. Cells use signaling pathways and regulatory mechanisms to coordinate multiple processes, allowing them to respond to and adapt to an ever-changing environ ..."
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Cited by 204 (6 self)
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A cell’s behavior is a consequence of the complex interactions between its numerous constituents, such as DNA, RNA, proteins and small molecules. Cells use signaling pathways and regulatory mechanisms to coordinate multiple processes, allowing them to respond to and adapt to an ever-changing environment. The large number of components, the degree of interconnectivity and the complex control of cellular networks are becoming evident in the integrated genomic and proteomic analyses that are emerging. It is increasingly recognized that the understanding of properties that arise from whole-cell function require integrated, theoretical descriptions of the relationships between different cellular components. Recent
STRING v9.1: protein-protein interaction networks, with increased coverage and integration
- Nucleic Acids Res
, 2013
"... Complete knowledge of all direct and indirect inter-actions between proteins in a given cell would represent an important milestone towards a com-prehensive description of cellular mechanisms and functions. Although this goal is still elusive, consid-erable progress has been made—particularly for ce ..."
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Cited by 180 (9 self)
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Complete knowledge of all direct and indirect inter-actions between proteins in a given cell would represent an important milestone towards a com-prehensive description of cellular mechanisms and functions. Although this goal is still elusive, consid-erable progress has been made—particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available inter-action data is desirable, including lower-quality data and/or computational predictions. The STRING database
Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography
- Cerebral Cortex
, 2009
"... Gaolang Gong and Yong He have contributed equally to this work The characterization of the topological architecture of complex networks underlying the structural and functional organization of the brain is a basic challenge in neuroscience. However, direct evidence for anatomical connectivity netwo ..."
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Cited by 107 (19 self)
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Gaolang Gong and Yong He have contributed equally to this work The characterization of the topological architecture of complex networks underlying the structural and functional organization of the brain is a basic challenge in neuroscience. However, direct evidence for anatomical connectivity networks in the human brain remains scarce. Here, we utilized diffusion tensor imaging deterministic tractography to construct a macroscale anatomical network capturing the underlying common connectivity pattern of human cerebral cortex in a large sample of subjects (80 young adults) and further quantitatively analyzed its topological properties with graph theoretical approaches. The cerebral cortex was divided into 78 cortical regions, each representing a network node, and 2 cortical regions were considered connected if the probability of fiber connections exceeded a statistical criterion. The topological parameters of the established cortical network (binarized) resemble that of a ''small-world'' architecture characterized by an exponentially truncated power-law distribution. These characteristics imply high resilience to localized damage. Furthermore, this cortical network was characterized by major hub regions in association cortices that were connected by bridge connections following long-range white matter pathways. Our results are compatible with previous structural and functional brain networks studies and provide insight into the organizational principles of human brain anatomical networks that underlie functional states.
Biological network comparison using graphlet degree distribution
- Bioinformatics
"... Motivation: Analogous to biological sequence comparison, comparing cellular networks is an important problem that could provide insight into biological understanding and therapeutics. For technical reasons, comparing large networks is computationally infeasible, and thus heuristics, such as the degr ..."
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Cited by 102 (1 self)
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Motivation: Analogous to biological sequence comparison, comparing cellular networks is an important problem that could provide insight into biological understanding and therapeutics. For technical reasons, comparing large networks is computationally infeasible, and thus heuristics, such as the degree distribution, clustering coefficient, diameter, and relative graphlet frequency distribution have been sought. It is easy to demonstrate that two networks are different by simply showing a short list of properties in which they differ. It is much harder to show that two networks are similar, as it requires demonstrating their similarity in all of their exponentially many properties. Clearly, it is computationally prohibitive to analyze all network properties, but the larger the number of constraints we impose in determining network similarity, the more likely it
Disrupted small-world networks in schizophrenia
- Brain, 131 (Pt
, 2008
"... The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates informationwith high efficiency.Many previous neuroimaging studies have provided consistent evidence of ‘dysfunctional connec ..."
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Cited by 95 (9 self)
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The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates informationwith high efficiency.Many previous neuroimaging studies have provided consistent evidence of ‘dysfunctional connectivity ’ among the brain regions in schizophrenia; however, little is known about whether or not this dysfunctional connectivity causes disruption of the topological properties of brain functional networks.To this end, we investigated the topological properties of human brain functional networks derived from resting-state functional magnetic resonance imaging (fMRI). Data was obtained from 31 schizophrenia patients and 31healthy subjects; then functional connectivity between 90 cortical and sub-cortical regions was estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. Our findings demonstrated that the brain functional networks had efficient small-world properties in the healthy subjects; whereas these properties were disrupted in the patients with schizophrenia. Brain functional networks have efficient small-world properties which support efficient parallel information transfer at a relatively low cost. More importantly, in patients with schizophrenia the small-world topological properties are significantly altered in many brain regions in the prefrontal, parietal and temporal
Pairwise global alignment of protein interaction networks by matching neighborhood topology
- Proceedings of the 11th Annual International Conference on Computational Molecular Biology (RECOMB’07
, 2007
"... Abstract. We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to max-imize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem | identify-ing many possible alignm ..."
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Cited by 90 (3 self)
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Abstract. We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to max-imize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem | identify-ing many possible alignments, each corresponding to a local region of similarity. IsoRank is guided by the intuition that a protein should be matched with a protein in the other network if and only if the neighbors of the two proteins can also be well matched. We encode this intuition as an eigenvalue problem, in a manner analogous to Google's PageRank method. We use IsoRank to compute the rst known global alignment between the S. cerevisiae and D. melanogaster PPI networks. The com-mon subgraph has 1420 edges and describes conserved functional compo-nents between the two species. Comparisons of our results with those of a well-known algorithm for local network alignment indicate that the glob-ally optimized alignment resolves ambiguity introduced by multiple local alignments. Finally, we interpret the results of global alignment to iden-tify functional orthologs between yeast and
y; our functional ortholog prediction method is much simpler than a recently proposed approach and yet provides results that are more comprehensive. 1
