Understanding Hierarchical Clustering Results by Interactive Exploration of Dendrograms: A Case Study with Genomic Microarray Data

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dc.contributor.authorSeo, Jinwooken_US
dc.contributor.authorShneiderman, Benen_US
dc.date.accessioned2004-05-31T23:18:49Z
dc.date.available2004-05-31T23:18:49Z
dc.date.created2002-05en_US
dc.date.issued2003-01-21en_US
dc.description.abstractAbstract: Hierarchical clustering is widely used to find patterns in multi-dimensional datasets, especially for genomic microarray data. Finding groups of genes with similar expression patterns can lead to better understanding of the functions of genes. Early software tools produced only printed results, while newer ones enabled some online exploration. We describe four general techniques that could be used in interactive explorations of clustering algorithms: (1) overview of the entire dataset, coupled with a detail view so that high-level patterns and hot spots can be easily found and examined, (2) dynamic query controls so that users can restrict the number of clusters they view at a time and show those clusters more clearly, (3) coordinated displays: the overview mosaic has a bi-directional link to 2-dimensional scattergrams, (4) cluster comparisons to allow researchers to see how different clustering algorithms group the genes. (UMIACS-TR-2002-50) (HCIL-TR-2002-10)en_US
dc.format.extent1373728 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/1203
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4370en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2002-50en_US
dc.relation.ispartofseriesHCIL-TR-2002-10en_US
dc.titleUnderstanding Hierarchical Clustering Results by Interactive Exploration of Dendrograms: A Case Study with Genomic Microarray Dataen_US
dc.typeTechnical Reporten_US

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