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  In silico promoter recognition from deepCAGE data

Yang, X., & Marsico, A. (2017). In silico promoter recognition from deepCAGE data. In U. A. Ørom (Ed.), Enhancer RNAs: Methods and Protocols. doi:10.1007/978-1-4939-4035-6_13.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-F6C6-B Version Permalink: http://hdl.handle.net/21.11116/0000-0000-F6CD-4
Genre: Book Chapter

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 Creators:
Yang, Xinyi1, Author              
Marsico, Annalisa2, 3, Author              
Affiliations:
1Computational Epigenetics (Ho-Ryun Chung), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479658              
2RNA Bioinformatics (Annalisa Marsico), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_2117285              
3Department of Mathematics and Informatics, Free University of Berlin, Berlin, 14195, Germany, ou_persistent22              

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Free keywords: DPI; PROmiRNA; Promoter; TSS; microRNAs
 Abstract: The accurate identification of transcription start regions corresponding to the promoters of known genes, novel coding, and noncoding transcripts, as well as enhancer elements, is a crucial step towards a complete understanding of state-specific gene regulatory networks. Recent high-throughput techniques, such as deepCAGE or single-molecule CAGE, have made it possible to identify the genome-wide location, relative expression, and differential usage of transcription start regions across hundreds of different tissues and cell lines. Here, we describe in detail the necessary computational analysis of CAGE data, with focus on two recent in silico methodologies for CAGE peak/profile definition and promoter recognition, namely the Decomposition-based Peak Identification (DPI) and the PROmiRNA software. We apply both methodologies to the challenging task of identifying primary microRNAs transcript (pri-miRNA) start sites and compare the results.

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Language(s): eng - English
 Dates: 2016-09-242017
 Publication Status: Published in print
 Pages: 29
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/978-1-4939-4035-6_13
 Degree: -

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Title: Enhancer RNAs: Methods and Protocols
Source Genre: Book
 Creator(s):
Ørom, Ulf Andersson1, Editor            
Affiliations:
1 Long non-coding RNA (Ulf Andersson Ørom), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479659            
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISBN: 978-1-4939-4035-6 (electronic) 978-1-4939-4033-2 (print)

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Title: Methods in Molecular Biology
Source Genre: Series
 Creator(s):
Walker, John M., Editor
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Publ. Info: New York : Humana Press
Pages: - Volume / Issue: 1468 Sequence Number: - Start / End Page: 171 - 199 Identifier: ISSN: 1940-6029 (electronic) 1064-3745 (print)