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dc.contributor.authorLoeliger, E.
dc.contributor.authorNehaniv, C.L.
dc.contributor.authorMunro, A. J.
dc.contributor.editorLones, Michael A.
dc.contributor.editorSmith, Stephen L.
dc.contributor.editorTeichmann, Sarah
dc.contributor.editorNaef, Felix
dc.contributor.editorWalker, James A.
dc.contributor.editorTrefzer, Martin A.
dc.date.accessioned2014-05-06T13:30:08Z
dc.date.available2014-05-06T13:30:08Z
dc.date.issued2012
dc.identifier.citationLoeliger , E , Nehaniv , C L & Munro , A J 2012 , Heat-maps and visualization for heterogeneous biomedical data based on information distance geometry . in M A Lones , S L Smith , S Teichmann , F Naef , J A Walker & M A Trefzer (eds) , Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer Nature , London , pp. 183-187 , 9th International Conference IPCAT 2012 , Cambridge , United Kingdom , 31/03/12 . https://doi.org/10.1007/978-3-642-28792-3_23
dc.identifier.citationconference
dc.identifier.isbn9783642287916
dc.identifier.isbn9783642287923
dc.identifier.otherPURE: 2153629
dc.identifier.otherPURE UUID: a172aae1-8936-45ff-9b54-5cfd9db99a98
dc.identifier.otherScopus: 84859134594
dc.identifier.urihttp://hdl.handle.net/2299/13485
dc.description.abstractSystems biology is very much concerned with gaining an overview of what is happening in complex systems, such as in biomedical data sets, for which we need good global visualization tools. This research uses a method based on information distance geometry to create visualizations analogous to heat-maps of prognostic and diagnostic variables. It illustrates the advantages of an informationally self-structuring approach to the understanding of biomedical data.en
dc.language.isoeng
dc.publisherSpringer Nature
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleHeat-maps and visualization for heterogeneous biomedical data based on information distance geometryen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionAdaptive Systems
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=84859134594&partnerID=8YFLogxK
rioxxterms.versionofrecordhttps://doi.org/10.1007/978-3-642-28792-3_23
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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