{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Muldoon SF"],"funding":["NICHD NIH HHS","NIDCD NIH HHS"],"pagination":["22057"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC4766852"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["6"],"pubmed_abstract":["Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this "],"journal":["Scientific reports"],"pubmed_title":["Small-World Propensity and Weighted Brain Networks."],"pmcid":["PMC4766852"],"funding_grant_id":["R01 DC009209","1R01HD086888-01","2-R01-DC-009209-11","R01 HD086888"],"pubmed_authors":["Muldoon SF","Bridgeford EW","Bassett DS"],"additional_accession":[]},"is_claimable":false,"name":"Small-World Propensity and Weighted Brain Networks.","description":"Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this ","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016 Feb","modification":"2025-04-25T17:33:46.015Z","creation":"2019-03-27T02:09:50Z"},"accession":"S-EPMC4766852","cross_references":{"pubmed":["26912196"],"doi":["10.1038/srep22057"]}}