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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/9882
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dc.contributor.authorMilagre, S. T.-
dc.contributor.authorMaciel, C. D.-
dc.contributor.authorShinoda, Ailton Akira-
dc.contributor.authorHungria, M.-
dc.contributor.authorAlmeida, J. R. B.-
dc.date.accessioned2014-05-20T13:29:21Z-
dc.date.available2014-05-20T13:29:21Z-
dc.date.issued2009-05-15-
dc.identifierhttp://dx.doi.org/10.1016/j.cam.2008.03.018-
dc.identifier.citationJournal of Computational and Applied Mathematics. Amsterdam: Elsevier B.V., v. 227, n. 2, p. 308-319, 2009.-
dc.identifier.issn0377-0427-
dc.identifier.urihttp://hdl.handle.net/11449/9882-
dc.description.abstractThe taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.en
dc.format.extent308-319-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.sourceWeb of Science-
dc.subjectCluster Analysisen
dc.subjectBrodyrhizobium Genusen
dc.subjectbioinformaticsen
dc.titleMultidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data seten
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Federal de Goiás (UFG)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionSoil Biotechnol Lab-
dc.description.affiliationUniv São Paulo, Dept Elect Engn, BR-13566590 São Carlos, SP, Brazil-
dc.description.affiliationGoias Fed Univ, Catalao, Brazil-
dc.description.affiliationState Univ São Paulo, Dept Elect Engn, Ilha Solteira, Brazil-
dc.description.affiliationSoil Biotechnol Lab, Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Soja, Londrina, Brazil-
dc.description.affiliationUnespState Univ São Paulo, Dept Elect Engn, Ilha Solteira, Brazil-
dc.identifier.doi10.1016/j.cam.2008.03.018-
dc.identifier.wosWOS:000265170000009-
dc.rights.accessRightsAcesso aberto-
dc.identifier.fileWOS000265170000009.pdf-
dc.relation.ispartofJournal of Computational and Applied Mathematics-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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