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Post-Transcriptional Gene Regulation

Overview of attention for book
Cover of 'Post-Transcriptional Gene Regulation'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction to Bioinformatics Resources for Post-transcriptional Regulation of Gene Expression.
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    Chapter 2 Post-Transcriptional Gene Regulation
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    Chapter 3 Transcriptional Regulation with CRISPR/Cas9 Effectors in Mammalian Cells.
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    Chapter 4 Studying the Translatome with Polysome Profiling.
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    Chapter 5 Exploring Ribosome Positioning on Translating Transcripts with Ribosome Profiling.
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    Chapter 6 Post-Transcriptional Gene Regulation
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    Chapter 7 Use of the pBUTR Reporter System for Scalable Analysis of 3' UTR-Mediated Gene Regulation.
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    Chapter 8 Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.
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    Chapter 9 Identifying RBP Targets with RIP-seq.
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    Chapter 10 PAR-CLIP: A Method for Transcriptome-Wide Identification of RNA Binding Protein Interaction Sites.
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    Chapter 11 Profiling the Binding Sites of RNA-Binding Proteins with Nucleotide Resolution Using iCLIP.
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    Chapter 12 A Pipeline for PAR-CLIP Data Analysis.
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    Chapter 13 Capture and Identification of miRNA Targets by Biotin Pulldown and RNA-seq.
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    Chapter 14 Post-Transcriptional Gene Regulation
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    Chapter 15 Genome-Wide Analysis of A-to-I RNA Editing.
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    Chapter 16 Nucleotide-Level Profiling of m5C RNA Methylation
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    Chapter 17 Probing N (6)-methyladenosine (m(6)A) RNA Modification in Total RNA with SCARLET.
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    Chapter 18 Genome-Wide Identification of Alternative Polyadenylation Events Using 3'T-Fill.
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    Chapter 19 Genome-Wide Profiling of Alternative Translation Initiation Sites.
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    Chapter 20 Post-Transcriptional Gene Regulation
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    Chapter 21 Visualizing mRNA Dynamics in Live Neurons and Brain Tissues.
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    Chapter 22 Single-Molecule Live-Cell Visualization of Pre-mRNA Splicing.
Attention for Chapter 12: A Pipeline for PAR-CLIP Data Analysis.
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Chapter title
A Pipeline for PAR-CLIP Data Analysis.
Chapter number 12
Book title
Post-Transcriptional Gene Regulation
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3067-8_12
Pubmed ID
26463385
Book ISBNs
978-1-4939-3066-1, 978-1-4939-3067-8
Authors

Jens, Marvin, Marvin Jens

Editors

Erik Dassi

Abstract

Photo-activatable ribonucleoside cross-linking and immunoprecipitation (PAR-CLIP) is a method to detect binding sites of RNA-binding proteins (RBPs) transcriptome-wide. This chapter covers the computational analysis of the high-throughput sequencing reads generated from PAR-CLIP experiments. It explains how the reads are mutated due to UV cross-linking and how to appropriately pre-process and align them to a reference sequence. Aligned reads are then aggregated into clusters which represent putative RBP-binding sites. Mapping artifacts are a source of false positives, which can be controlled by means of a mapping decoy and adaptive quality filtering of the read clusters. A step-by-step explanation of this procedure is given. All necessary tools are open source, including the scripts presented and used in this chapter.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 25%
Researcher 8 20%
Student > Master 5 13%
Student > Doctoral Student 3 8%
Professor 1 3%
Other 1 3%
Unknown 12 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 43%
Agricultural and Biological Sciences 9 23%
Computer Science 1 3%
Neuroscience 1 3%
Unknown 12 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 October 2015.
All research outputs
#15,348,897
of 22,830,751 outputs
Outputs from Methods in molecular biology
#5,344
of 13,126 outputs
Outputs of similar age
#230,863
of 393,540 outputs
Outputs of similar age from Methods in molecular biology
#545
of 1,470 outputs
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So far Altmetric has tracked 13,126 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,470 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.

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