Interactively exploring hierarchical clustering results [gene identification]

TitleInteractively exploring hierarchical clustering results [gene identification]
Publication TypeJournal Articles
Year of Publication2002
AuthorsSeo J, Shneiderman B
Pagination80 - 86
Date Published2002/07//
ISBN Number0018-9162
Keywordsalgorithmic methods, arrays, Bioinformatics, biological data sets, biology computing, Data analysis, data mining, data visualisation, Data visualization, DNA, Fluorescence, gene functions, gene identification, gene profiles, Genetics, Genomics, Hierarchical Clustering Explorer, hierarchical systems, interactive exploration, interactive information visualization tool, interactive systems, Large screen displays, meaningful cluster identification, metrics, microarray data analysis, pattern clustering, pattern extraction, Process control, Sensor arrays, sequenced genomes, Tiles

To date, work in microarrays, sequenced genomes and bioinformatics has focused largely on algorithmic methods for processing and manipulating vast biological data sets. Future improvements will likely provide users with guidance in selecting the most appropriate algorithms and metrics for identifying meaningful clusters-interesting patterns in large data sets, such as groups of genes with similar profiles. Hierarchical clustering has been shown to be effective in microarray data analysis for identifying genes with similar profiles and thus possibly with similar functions. Users also need an efficient visualization tool, however, to facilitate pattern extraction from microarray data sets. The Hierarchical Clustering Explorer integrates four interactive features to provide information visualization techniques that allow users to control the processes and interact with the results. Thus, hybrid approaches that combine powerful algorithms with interactive visualization tools will join the strengths of fast processors with the detailed understanding of domain experts