| Mesoscopic analysis of networks: Applications to exploratory analysis and data clustering. | |
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MedLine Citation:
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PMID: 21456844 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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We investigate the adaptation and performance of modularity-based algorithms, designed in the scope of complex networks, to analyze the mesoscopic structure of correlation matrices. Using a multiresolution analysis, we are able to describe the structure of the data in terms of clusters at different topological levels. We demonstrate the applicability of our findings in two different scenarios: to analyze the neural connectivity of the nematode Caenorhabditis elegans and to automatically classify a typical benchmark of unsupervised clustering, the Iris dataset, with considerable success. |
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Authors:
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Clara Granell; Sergio Gómez; Alex Arenas |
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Publication Detail:
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Type: JOURNAL ARTICLE |
Journal Detail:
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Title: Chaos (Woodbury, N.Y.) Volume: 21 ISSN: 1089-7682 ISO Abbreviation: - Publication Date: 2011 Mar |
Date Detail:
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Created Date: 2011-4-4 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 100971574 Medline TA: Chaos Country: - |
Other Details:
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Languages: ENG Pagination: 016102 Citation Subset: - |
Affiliation:
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Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona, Catalonia, Spain. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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