Applying weighted network measures to microarray distance matrices

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dc.creatorAhnert, S. E.
dc.creatorGarlaschelli, D.
dc.creatorFink, T. M. A.
dc.creatorCaldarelli, G.
dc.date2008-03-10
dc.date.accessioned2026-07-07T09:42:32Z
dc.date.available2026-07-07T09:42:32Z
dc.descriptionIn recent work we presented a new approach to the analysis of weighted networks, by providing a straightforward generalization of any network measure defined on unweighted networks. This approach is based on the translation of a weighted network into an ensemble of edges, and is particularly suited to the analysis of fully connected weighted networks. Here we apply our method to several such networks including distance matrices, and show that the clustering coefficient, constructed by using the ensemble approach, provides meaningful insights into the systems studied. In the particular case of two data sets from microarray experiments the clustering coefficient identifies a number of biologically significant genes, outperforming existing identification approaches.
dc.descriptionAccepted for publication in J. Phys. A
dc.identifierhttps://arxiv.org/abs/0803.1459
dc.identifierhttp://arxiv.org/abs/0803.1459
dc.identifierJ. Phys. A: Math. Theor. 41, 224011 (2008)
dc.identifierdoi:10.1088/1751-8113/41/22/224011
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/162214
dc.subjectData Analysis, Statistics and Probability
dc.subjectBiological Physics
dc.subjectQuantitative Methods
dc.titleApplying weighted network measures to microarray distance matrices
dc.typetext

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