relation: http://eprints.imtlucca.it/1094/
title: Applying weighted network measures to microarray distance matrices
creator: Ahnert, Sebastian E.
creator: Garlaschelli, Diego
creator: Fink, Thomas M.A.
creator: Caldarelli, Guido
subject: QA Mathematics
subject: QC Physics
subject: QH301 Biology
description: In 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 datasets from microarray experiments the clustering coefficient identifies a number of biologically significant genes, outperforming existing identification approaches.
publisher: Institute of Physics
date: 2008-06
type: Article
type: PeerReviewed
identifier:   Ahnert, Sebastian E. and Garlaschelli, Diego and Fink, Thomas M.A. and Caldarelli, Guido  Applying weighted network measures to microarray distance matrices.  Journal of Physics A: Mathematical and Theoretical, 41 (22).  p. 224011.  ISSN 1751-8113      (2008)  
relation: http://dx.doi.org/10.1088/1751-8113/41/22/224011
relation: 10.1088/1751-8113/41/22/224011