Type
Book ChapterKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionComputational Bioscience Research Center (CBRC)
Biological and Environmental Sciences and Engineering (BESE) Division
Bioscience Program
Applied Mathematics and Computational Science Program
Date
2009-10-01Permanent link to this record
http://hdl.handle.net/10754/575855
Metadata
Show full item recordAbstract
Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.ISBN
9789814241342ae974a485f413a2113503eed53cd6c53
10.4032/9789814241359