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Biclustering of Time Series Microarray Data

  • Jia Meng
  • Yufei HuangEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 802)

Abstract

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.

Key words

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

Notes

Acknowledgments

This work is supported by an NSF Grant CCF-0546345.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of Texas at San AntonioSan AntonioUSA
  2. 2.Greehey Children’s Cancer Research InstituteUniversity of Texas Health Science Center at San AntonioSan AntonioUSA

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