Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/3006
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dc.contributor.authorSchroeder, M-
dc.contributor.authorGilbert, D-
dc.contributor.authorHelden, JV-
dc.contributor.authorNoy, P-
dc.date.accessioned2009-01-30T17:17:05Z-
dc.date.available2009-01-30T17:17:05Z-
dc.date.issued2001-
dc.identifier.citationInformation Sciences. 139(1): 19-57en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/3006-
dc.description.abstractWith the data explosion in biology visualisation techniques are of paramount importance for further progress. In this paper, we present a framework to characterise the visualisation process. We identify two main data types and introduce structure comparison data and gene expression data as representatives, which serve as running examples throughout. Next, we review various distance measures and develop a design methodology for distances. We critically review the classical approach of clustering and visualisation through trees, in particular dendrograms, and pinpoint shortcomings of this technique. In order to tackle these shortcomings, we survey information visualisation techniques and we discuss an alternative approach and system: Space Explorer, which maps the relationships of objects to distances and visualizes these distances in a 3D, interactive space. We evaluate three layout algorithms for the two data types and apply them to our case studies.en
dc.format.extent278 bytes-
dc.format.mimetypetext/plain-
dc.language.isoen-
dc.publisherElsevieren
dc.titleApproaches to visualisation in bioinformatics: From dendrograms to space exploreren
dc.typeResearch Paperen
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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