Clustering gene expression data with temporal abstractions

L. Sacchi, R. Bellazzi, C. Larizza, P. Magni, T. Curk, U. Petrovic, B. Zupan

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper describes a new technique for clustering short time series comingfrom gene expression data. The technique is based on the labelling of the time series through temporal trend abstractions and a consequent clustering of the series on the basis of their labels. Clustering is performed at three different levels of aggregation of the original time series, so that the results are organized and visualized as a three-levels hierarchical tree. Results on simulated and on yeast data are shown. The technique appears robust and efficient and the results obtained are easy to be interpreted.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Pages798-802
Number of pages5
Volume107
DOIs
Publication statusPublished - 2004

Keywords

  • Bioinfonnatics
  • cluster analysis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Sacchi, L., Bellazzi, R., Larizza, C., Magni, P., Curk, T., Petrovic, U., & Zupan, B. (2004). Clustering gene expression data with temporal abstractions. In Studies in Health Technology and Informatics (Vol. 107, pp. 798-802) https://doi.org/10.3233/978-1-60750-949-3-798