An Entropy-Based Graph Construction Method for Representing and Clustering Biological Data

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dc.citation.journalTitleIfmbe Proceedings
dc.contributor.authorAriza-Jiménez L.
dc.contributor.authorPinel N.
dc.contributor.authorVilla L.F.
dc.contributor.authorQuintero O.L.
dc.contributor.departmentUniversidad EAFIT. Departamento de Cienciasspa
dc.contributor.researchgroupBiodiversidad, Evolución y Conservaciónspa
dc.date.accessioned2021-03-23T19:52:10Z
dc.date.available2021-03-23T19:52:10Z
dc.date.issued2019-10-01
dc.description.abstractUnsupervised learning methods are commonly used to perform the non-trivial task of uncovering structure in biological data. However, conventional approaches rely on methods that make assumptions about data distribution and reduce the dimensionality of the input data. Here we propose the incorporation of entropy related measures into the process of constructing graph-based representations for biological datasets in order to uncover their inner structure. Experimental results demonstrated the potential of the proposed entropy-based graph data representation to cope with biological applications related to unsupervised learning problems, such as metagenomic binning and neuronal spike sorting, in which it is necessary to organize data into unknown and meaningful groups. © 2020, Springer Nature Switzerland AG.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=9841
dc.identifier.doi10.1007/978-3-030-30648-9_41
dc.identifier.issn16800737
dc.identifier.otherSCOPUS;2-s2.0-85075700831
dc.identifier.urihttp://hdl.handle.net/10784/26750
dc.language.isoengeng
dc.publisherSPRINGER
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075700831&doi=10.1007%2f978-3-030-30648-9_41&partnerID=40&md5=930b9690370f241ec1412784c1f71f70
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/1680-0737
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccesseng
dc.rights.localAcceso restringidospa
dc.sourceIfmbe Proceedings
dc.subjectBiomedicaleng
dc.subjectengineeringeng
dc.subjectBiophysicseng
dc.subjectEntropyeng
dc.subjectGraphiceng
dc.subjectmethodseng
dc.subjectMachineeng
dc.subjectlearningeng
dc.subjectUnsupervisedeng
dc.subjectlearningeng
dc.subjectBiologicaleng
dc.subjectdataeng
dc.subjectClusteringeng
dc.subjectGrapheng
dc.subjectMetagenomiceng
dc.subjectbinningeng
dc.subjectSpike-sortingeng
dc.subjectSortingeng
dc.titleAn Entropy-Based Graph Construction Method for Representing and Clustering Biological Dataeng
dc.typepublishedVersioneng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.type.localArtículospa

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