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Chapter category: Bioinformatics
Model-Based Inference of Transcriptional Regulatory Mechanisms from DNA Microarray Data
Chapter authors:
Harmen J. Bussemaker
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The development of DNA microarray technology has made it possible to monitor the
mRNA abundance of all genes simultaneously (the transcriptome) for a variety of
cellular conditions. In addition, microarray-based genomewide measurements of promoter
occupancy (the occupome) are now available for an increasing number of transcription
factors. With this data and the complete genome sequence of many important organisms, it is
becoming possible to quantitatively model the molecular computation performed at each promoter,
which has as input the nuclear concentration of the active form of various regulatory
proteins (the regulome) and as output a transcription rate, which in turn determines mRNA
abundance. In this chapter, we describe how our group has used multivariate linear regression
methods to: (i) discover cis-regulatory elements in upstream regulatory regions in an unbiased
manner; (ii) infer a regulatory activity profile across conditions for each transcription factor;
and (iii) determine whether the mRNA expression level of a gene whose promoter is occupied
by a particular transcription factor is truly regulated by that factor, through integrated modeling
of expression and promoter occupancy data. Together, these results show model-based
analysis of functional genomics data to be a versatile conceptual and practical framework for
the elucidation of regulatory circuitry, and a powerful alternative to the currently prevalent
clustering-based methods.
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