<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>12(1)</volume><submitter>Ashtiani M</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Numerous centrality measures have been introduced to identify "central" nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins. We studied how different topological network features are reflected in a large set of commonly used centrality measures.&lt;h4>Results&lt;/h4>We</pubmed_abstract><journal>BMC systems biology</journal><pagination>80</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6069823</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A systematic survey of centrality measures for protein-protein interaction networks.</pubmed_title><pmcid>PMC6069823</pmcid><pubmed_authors>Wolkenhauer O</pubmed_authors><pubmed_authors>Mirzaie M</pubmed_authors><pubmed_authors>Jafari M</pubmed_authors><pubmed_authors>Ashtiani M</pubmed_authors><pubmed_authors>Razaghi-Moghadam Z</pubmed_authors><pubmed_authors>Salehzadeh-Yazdi A</pubmed_authors><pubmed_authors>Hennig H</pubmed_authors></additional><is_claimable>false</is_claimable><name>A systematic survey of centrality measures for protein-protein interaction networks.</name><description>&lt;h4>Background&lt;/h4>Numerous centrality measures have been introduced to identify "central" nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins. We studied how different topological network features are reflected in a large set of commonly used centrality measures.&lt;h4>Results&lt;/h4>We</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Jul</publication><modification>2025-04-04T20:30:47.492Z</modification><creation>2019-03-26T23:49:58Z</creation></dates><accession>S-EPMC6069823</accession><cross_references><pubmed>30064421</pubmed><doi>10.1186/s12918-018-0598-2</doi></cross_references></HashMap>