Functional topology in a network of protein interactions

By Natasa Przulj, Dennis A. Wigle, Igor Jurisica. Bioinform., 2004

449 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8964e7215d896199afd620a35411e6ed7b4d79b8

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In Molecular Biology

Citations in the corpus

Uncovering Biological Network Function via Graphlet Degree Signatures (2008, methodology): ““Krogan” is the “core” PPI data set containing 7,123 interactions amongst 2,708 proteins obtained by TAP experiments as described by Krogan et al. (Krogan et al., 2006).”
Functional and evolutionary inference in gene networks: does topology matter? (2006, methodology): “The essentiality prediction has been tested for the yeast protein-interaction network, by comparing each protein’s number of connections to its effect on cell viability when absent (by gene deletion) (Jeong et al. 2001; Pržulj et al. 2004; Hahn and Kern 2005).”
Network-based prediction of protein function (2007, methodology): “Przulj et al (2004) used the highly connected subgraphs (HCS) algorithm (Hartuv and Shamir, 2000) to determine complexes in PPI data.”
Automated Network Analysis Identifies Core Pathways in Glioblastoma (2010, background): “This community structure or network modularity has been identified in diverse network systems, including social [18,19], scientific collaboration [20], metabolic [21], and molecular interaction networks [22–24].”
Protein-to-protein interactions: Technologies, databases, and algorithms (2010, methodology): “The extraction of global properties aimed to represent PPI networks by using models used in yet other .elds, such as random graphs or scale-free networks [Albert 2005; Erdos and Renyi 1960; Przulj et al. 2004].”
Graph theory and networks in Biology. (2006, methodology): “Finally, we note another measure of importance in biological networks which was recently described in [149].”
Computational approaches for detecting protein complexes from protein interaction networks: a survey (2010, background): “The statistical significance of the occurrence of a protein cluster (predicted protein complex) with respect to a given functional annotation can be computed by the following hypergeometric distribution in equation (9) [88,89]:”