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Inferring the underlying multivariate structure from bivariate networks with highly correlated nodes

dc.contributor.authorLoske, Philipp
dc.contributor.authorSchelter, Bjoern O.
dc.date.accessioned2022-11-17T00:10:20Z
dc.date.available2022-11-17T00:10:20Z
dc.date.issued2022-07
dc.identifier218808867
dc.identifier235a5895-406a-40c2-830a-f7c40da0d0b6
dc.identifier85134620398
dc.identifier35864116
dc.identifier.citationLoske , P & Schelter , B O 2022 , ' Inferring the underlying multivariate structure from bivariate networks with highly correlated nodes ' , Scientific Reports , vol. 12 , no. 1 , 12486 . https://doi.org/10.1038/s41598-022-16296-yen
dc.identifier.issn2045-2322
dc.identifier.urihttp://aura-test.abdn.ac.uk/handle/2164/19288
dc.descriptionFunding Information: PL acknowledges financial support from Medical Research Scotland (Grant No.: RG14565).en
dc.format.extent12
dc.format.extent2455357
dc.language.isoeng
dc.relation.ispartofScientific Reportsen
dc.subjectApplied mathematicsen
dc.subjectComplex networksen
dc.subjectstatisticsen
dc.subjectQC Physicsen
dc.subjectGeneralen
dc.subjectOtheren
dc.subjectRG14565en
dc.subject.lccQCen
dc.titleInferring the underlying multivariate structure from bivariate networks with highly correlated nodesen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Aberdeen Biomedical Imaging Centreen
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.contributor.institutionUniversity of Aberdeen.Physicsen
dc.description.statusPeer revieweden
dc.identifier.doi10.1038/s41598-022-16296-y
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85134620398&partnerID=8YFLogxKen


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