Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks.

By Matthew W. Hahn, Andrew D. Kern. Molecular biology and evolution, 2005

655 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/727452d7a24ce203f68265f89051813193eb9110

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Citations in the corpus

Why Do Hubs in the Yeast Protein Interaction Network Tend To Be Essential: Reexamining the Connection between the Network Topology and Essentiality (2008, result): “Since then the correlation between degree and essentiality was confirmed by other studies [4–7], but until recently there was no systematic attempt to examine the reasons for this correlation.”
Functional and evolutionary inference in gene networks: does topology matter? (2006, methodology): “the probability of a protein’s being essential, even after the effect of node degree is removed statistically (Hahn and Kern 2005).”
Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks (2008, methodology): “Another study by Hahn and Kern (2005) compared three centralities (degree, closeness and betweenness) for the identi ﬁ cation of essential proteins in three different organisms: Saccharomyces cerevisiae , Caenorhabditis elegans , and Drosophila melanogaster .”
Using graph theory to analyze biological networks (2011, background): “The coupling between centrality and essentiality has also been investigated in several eukaryotic protein networks [94].”
Centrality measures and the importance of generalist species in pollination networks (2010, background): “species with a high generalization level) have on average shorter distances to the rest of the nodes in the network, as shown in several ecological and non-ecological studies (Dunne et al., 2002; Goh et al., 2002; Guimerà and Amaral, 2004; Hahn and Kerns, 2004; Memmott et al., 2004; Jordán et al., 2”
Network pharmacology: the next paradigm in drug discovery. (2008, background): “Bottlenecks with high betweenness values tend to be better correlated with gene expression dynamics and essentiality than highly connected hub”
Gene network interconnectedness and the generalized topological overlap measure (2007, background): “Knock-out experiments in lower organisms (e.g. yeast, fly, worm) have shown that essential proteins tend to be more highly connected than non-essential proteins [7-9].”
The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics (2007, background): “We found that bottlenecks in both regulatory and interaction networks indeed tend to be essential proteins with high signiﬁcance (see Figure 2A), in agreement with previous studies [18,19].”
SINCERA: A Pipeline for Single-Cell RNA-Seq Profiling Analysis (2015, background): “Network node importance is determined by measuring centrality and/ or disruption [61,62].”
Identifying gene-disease associations using centrality on a literature mined gene-interaction network (2008, background): “For example, Jeong et al. (2001) studied the protein–protein interaction network of yeast in order to predict lethal mutations. They showed that the network is tolerant to random errors, whereas errors related to the most central proteins (in terms of degree) cause lethality. Similarly, Joy et al. (”
Flexible nets: disorder and induced fit in the associations of p53 and 14-3-3 with their partners (2008, result): “From this body of work, hub proteins appear to evolve more slowly than non-hub proteins, an observation that is consistent with Fisher's classic proposal that pleiotropy constrains evolution [14,15].”
Why Do Hubs Tend to Be Essential in Protein Networks? (2006, neutral): “That is, functional importance of a node is thought to arise from its structural importance in the network [6,7,9,10].”
Flexible nets (2005, result): “These observations are consistent with Fisher’s classic proposal that pleiotropy constrains evolution [24,25].”
Evolutionary and Physiological Importance of Hub Proteins (2006, critical): “[14] have suggested that prior claims for such a relationship [7–10] may be dataset artifacts.”
The Multipredator Hypothesis and the Evolutionary Persistence of Antipredator Behavior (2006, background): “At the genomic level proteins that are centrally located in networks (Hahn & Kern 2004) are buffered from change, and this centrality may provide a mechanism by which pleiotropy may constrain the rate of evolutionary change.”
Social network theory: new insights and issues for behavioral ecologists (2009, methodology): “2005) including gene or protein networks (Lee et al. 2002; Barabási and Oltvai 2004; Hahn and Kern 2005; Stumpf et al. 2007), neural networks (Loughlin and Sejnowski 2003; Sporns and Kotter 2004; Humphries et al.”