Biclustering of time series microarray data

Jia Meng, Yufei Huang*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)


Clustering is a popular data exploration technique widely used in microarray data analysis. In this chapter, we review ideas and algorithms of bicluster and its applications in time series microarray analysis. We introduce first the concept and importance of biclustering and its different variations. We then focus our discussion on the popular iterative signature algorithm (ISA) for searching biclusters in microarray dataset. Next, we discuss in detail the enrichment constraint time-dependent ISA (ECTDISA) for identifying biologically meaningful temporal transcription modules from time series microarray dataset. In the end, we provide an example of ECTDISA application to time series microarray data of Kaposi's Sarcoma-associated Herpesvirus (KSHV) infection.

Original languageEnglish
Title of host publicationNext Generation Microarray Bioinformatics
Subtitle of host publicationMethods and Protocols
EditorsJunbai Wang, Tianhai Tian, Aik Choon Tan
Number of pages14
Publication statusPublished - 2012
Externally publishedYes

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745


  • Bicluster
  • Clustering
  • Enrichment constrained
  • Iterative signature algorithm
  • Microarray
  • Temporal module
  • Time dependent
  • Time series

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