Lethality and centrality in protein networks

By Hawoong Jeong, S. Mason, Albert-László Barabási, Zoltn Oltvai. 2001

5,243 citations recorded by the source corpus.

Proteins are traditionally identified on the basis of their individual actions as catalysts, signalling molecules, or building blocks in cells and microorganisms. But our post-genomic view is expanding the protein's role into an element in a network of protein–protein interactions as well, in which it has a contextual or cellular function within functional modules. Here we provide quantitative support for this idea by demonstrating that the phenotypic consequence of a single gene deletion in the yeast Saccharomyces cerevisiae is affected to a large extent by the topological position of its protein product in the complex hierarchical web of molecular interactions.

Subfields: Molecular Biology

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In Molecular Biology

Citations in the corpus

Mining communities and their relationships in blogs: A study of online hate groups (2007, background): “Most empirical networks ranging from social networks (Newman, 2004a), biological networks (Jeong et al., 2001), to the Web (Albert et al., 1999) have been found to be nonrandom networks.”
Network structure and biodiversity loss in food webs: robustness increases with connectance (2002, background): “The extreme susceptibility of power-law networks to removal of the most connected nodes has been found in Internet, WWW, metabolic, and protein networks (Albert et al. 2000; Jeong et al. 2000, 2001).”
Partial Correlation Estimation by Joint Sparse Regression Models (2008, background): “For instance, it has been shown that most genetic networks are intrinsically sparse (Gardner et al. 2003; Jeong et al. 2001; Tegner et al. 2003).”
cytoHubba: identifying hub objects and sub-networks from complex interactome (2014, methodology): “The plugin implements eleven node ranking methods to evaluate the importance of nodes in a biological network including Degree [1], Edge Percolated Component [9], Maximum Neighborhood Component [10], Density of Maximum Neighborhood Component [10], Maximal Clique Centrality (proposed in this paper),…”
An automated method for finding molecular complexes in large protein interaction networks (2003, positive): “Recent research on modeling complex systems [21,25,27] has found that networks such as the world wide web, metabolic networks [26] and protein-protein interaction networks [36] are scale-free.”
DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions (2002, background): “During the last 3 years protein interaction databases have grown to the point of becoming both a commonly used reference source for experimental biologists (1–3), as well as a data source enabling studies of the properties and structure of entire protein interaction networks ( 4 ).”
Metabolomics in systems biology. (2003, methodology): “By using metabolic reconstruction based on genome annotation or biochemical knowledge, researchers can investigate theoretical networks and their structural features (1, 19, 46, 47, 80).”
A travel guide to Cytoscape plugins (2012, methodology): “The NetworkAnalyzer 23 plugin is installed in Cytoscape by default and calculates network metrics such as the distribution of node degrees (node degree refers to the number of interactions involving a node; it has been shown to correlate with the essential status of genes 24 ).”
The Network Structure of Food Webs (2005, neutral): “About that time, a series of papers examined the response of a variety of networks including the Internet and WWW pages (Albert et al. 2000) and metabolic and protein networks (Jeong et al. 2000, 2001) to the simulated loss of nodes.”
Evidence for dynamically organized modularity in the yeast protein–protein interaction network (2004, neutral): “jpg" NDATA ITEM> ]> In apparently scale-free protein–protein interaction networks, or ‘interactome’ network”
Attack Robustness and Centrality of Complex Networks (2013, background): “…network of the nematode C. elegans [1,34], the power grid of the western United States [1], the protein-protein interaction network of the yeast S. cerevisiae [35], a dolphin social network [36], a high-energy physics collaboration network [37], and a network science collaboration network [38].”