Transcription regulatory networks analysis using CAGE

Handle URI:
http://hdl.handle.net/10754/575855
Title:
Transcription regulatory networks analysis using CAGE
Authors:
Tegnér, Jesper N.; Björkegren, Johan L M; Ravasi, Timothy ( 0000-0002-9950-465X ) ; Bajic, Vladimir
Abstract:
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.
KAUST Department:
Computational Bioscience Research Center (CBRC)
Journal:
Cap-Analysis Gene Expression (CAGE): The Science of Decoding Genes Transcription
Issue Date:
1-Oct-2009
DOI:
10.4032/9789814241359
Type:
Book Chapter
ISBN:
9789814241342
Appears in Collections:
Computational Bioscience Research Center (CBRC); Book Chapters

Full metadata record

DC FieldValue Language
dc.contributor.authorTegnér, Jesper N.en
dc.contributor.authorBjörkegren, Johan L Men
dc.contributor.authorRavasi, Timothyen
dc.contributor.authorBajic, Vladimiren
dc.date.accessioned2015-08-24T09:55:37Zen
dc.date.available2015-08-24T09:55:37Zen
dc.date.issued2009-10-01en
dc.identifier.isbn9789814241342en
dc.identifier.doi10.4032/9789814241359en
dc.identifier.urihttp://hdl.handle.net/10754/575855en
dc.description.abstractMapping 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.en
dc.titleTranscription regulatory networks analysis using CAGEen
dc.typeBook Chapteren
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.identifier.journalCap-Analysis Gene Expression (CAGE): The Science of Decoding Genes Transcriptionen
dc.contributor.institutionKing Gustaf V Research Institute, Karolinska Institutet, Swedenen
dc.contributor.institutionDepartment of Physics, Linköping University, Swedenen
dc.contributor.institutionScripps Neuro AIDS Preclinical Studies (SNAPS), United Statesen
dc.contributor.institutionJacobs School of Engineering, University of California, United Statesen
dc.contributor.institutionSouth African National Bioinformatics Institute (SANBI), University of Western Cape, Saudi Arabiaen
kaust.authorRavasi, Timothyen
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