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

dc.creatorAriza-Jiménez L.
dc.creatorPinel N.
dc.creatorVilla L.F.
dc.creatorQuintero O.L.
dc.date2020
dc.date.accessioned2020-04-29T14:53:34Z
dc.date.available2020-04-29T14:53:34Z
dc.identifier.isbn9783030306472
dc.identifier.issn16800737
dc.identifier.urihttp://hdl.handle.net/11407/5648
dc.descriptionUnsupervised 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.
dc.language.isoeng
dc.publisherSpringer
dc.relation.isversionofhttps://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.sourceIFMBE Proceedings
dc.subjectBiological data
dc.subjectClustering
dc.subjectEntropy
dc.subjectGraph
dc.subjectMetagenomic binning
dc.subjectSpike sorting
dc.subjectBiomedical engineering
dc.subjectBiophysics
dc.subjectEntropy
dc.subjectGraphic methods
dc.subjectMachine learning
dc.subjectUnsupervised learning
dc.subjectBiological data
dc.subjectClustering
dc.subjectGraph
dc.subjectMetagenomic binning
dc.subjectSpike-sorting
dc.subjectSorting
dc.titleAn Entropy-Based Graph Construction Method for Representing and Clustering Biological Data
dc.typeConference Papereng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemas
dc.identifier.doi10.1007/978-3-030-30648-9_41
dc.relation.citationvolume75
dc.relation.citationstartpage315
dc.relation.citationendpage321
dc.publisher.facultyFacultad de Ingenierías
dc.affiliationAriza-Jiménez, L., Mathematical Modeling Research Group, Universidad EAFIT, Medellí­n, Colombia; Pinel, N., Biodiversity, Evolution, and Conservation Research Group, Universidad EAFIT, Medellí­n, Colombia; Villa, L.F., System Engineering Research Group, ARKADIUS, Universidad de Medellí­n, Medellí­n, Colombia; Quintero, O.L., Mathematical Modeling Research Group, Universidad EAFIT, Medellí­n, Colombia
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dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/article


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