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Exploring biological data : Mappings between ontology- and cluster-based representations

Exploring biological data : Mappings between ontology- and cluster-based representations


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JUSUFI, Ilir, Andreas KERREN, Falk SCHREIBER, 2013. Exploring biological data : Mappings between ontology- and cluster-based representations. In: Information Visualization. 12(3-4), pp. 291-307. ISSN 1473-8716. eISSN 1473-8724

@article{Jusufi2013-07-29Explo-38244, title={Exploring biological data : Mappings between ontology- and cluster-based representations}, year={2013}, doi={10.1177/1473871612468880}, number={3-4}, volume={12}, issn={1473-8716}, journal={Information Visualization}, pages={291--307}, author={Jusufi, Ilir and Kerren, Andreas and Schreiber, Falk} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/38244"> <dcterms:rights rdf:resource="http://nbn-resolving.de/urn:nbn:de:bsz:352-20150914100631302-4485392-8"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-03-31T09:50:17Z</dc:date> <dc:contributor>Kerren, Andreas</dc:contributor> <dcterms:title>Exploring biological data : Mappings between ontology- and cluster-based representations</dcterms:title> <dcterms:issued>2013-07-29</dcterms:issued> <dc:creator>Schreiber, Falk</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-03-31T09:50:17Z</dcterms:available> <dc:language>eng</dc:language> <dc:creator>Kerren, Andreas</dc:creator> <dc:contributor>Jusufi, Ilir</dc:contributor> <dc:creator>Jusufi, Ilir</dc:creator> <dcterms:abstract xml:lang="eng">Ontologies and hierarchical clustering are both important tools in biology and medicine to study high-throughput data such as transcriptomics and metabolomics data. Enrichment of ontology terms in the data is used to identify statistically overrepresented ontology terms, giving insight into relevant biological processes or functional modules. Hierarchical clustering is a standard method to analyze and visualize data to find relatively homogeneous clusters of experimental data points. Both methods support the analysis of the same data set but are usually considered independently. However, often a combined view is desired: visualizing a large data set in the context of an ontology under consideration of a clustering of the data. This article proposes new visualization methods for this task. They allow for interactive selection and navigation to explore the data under consideration as well as visual analysis of mappings between ontology- and cluster-based space-filling representations. In this context, we discuss our approach together with specific properties of the biological input data and identify features that make our approach easily usable for domain experts.</dcterms:abstract> <dc:contributor>Schreiber, Falk</dc:contributor> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/38244"/> </rdf:Description> </rdf:RDF>

Dateiabrufe seit 31.03.2017 (Informationen über die Zugriffsstatistik)

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