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Predictive Models of Gene Regulation

Application of Regression Methods to Microarray Data

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Part of the Methods in Molecular Biology™ book series (MIMB,volume 377)

Abstract

Eukaryotic transcription is a complex process. A myriad of biochemical signals cause activators and repressors to bind specific cis-elements on the promoter DNA, which help to recruit the basal transcription machinery that ultimately initiates transcription. In this chapter, we discuss how regression techniques can be effectively used to infer the functional cis-regulatory elements and their cooperativity from microarray data. Examples from yeast cell cycle are drawn to demonstrate the power of these techniques. Periodic regulation of the cell cycle, connection with underlying energetics, and the inference of combinatorial logic are also discussed. An implementation based on regression splines is discussed in detail.

Key Words

  • Transcription regulation
  • regression
  • splines
  • cooperativity
  • correlation
  • yeast
  • cell cycle
  • cis-regulatory element
  • MARS

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© 2007 Humana Press Inc., Totowa, NJ

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Das, D., Zhang, M.Q. (2007). Predictive Models of Gene Regulation. In: Korenberg, M.J. (eds) Microarray Data Analysis. Methods in Molecular Biology™, vol 377. Humana Press. https://doi.org/10.1007/978-1-59745-390-5_5

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  • DOI: https://doi.org/10.1007/978-1-59745-390-5_5

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-540-8

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