Approaches to visualisation in bioinformatics: from dendrograms to Space Explorer

With the data explosion in biology visualisation techniques are of paramount importance for further progress. In this paper, we review traditional visualisation by clustering and dendrogram, which are prevailent in biology. We discuss its shortcomings and develop an alternative approach: Space Explorer 1 . In detail, we first 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 develop an alternative approach and system: Space Explorer, which maps the relationships of objects to distances and visualises these distances in a 3D, interactive space. We develop and evaluate three layout algorithms for the two data types and apply them to our case studies.