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Post-Transcriptional Gene Regulation

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

Table of Contents

  1. Altmetric Badge
    Book Overview
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    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.
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

18 tweeters

Readers on

20 Mendeley
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Post-Transcriptional Gene Regulation
Published by
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3067-8
Pubmed ID
978-1-4939-3066-1, 978-1-4939-3067-8

Erik Dassi, Sibbritt, Tennille, Shafik, Andrew, Clark, Susan J, Preiss, Thomas, Dassi, Erik


Erik Dassi


Mapping the position and quantifying the level of 5-methylcytosine (m(5)C) as a modification in different types of cellular RNA is an important objective in the emerging field of epitranscriptomics. Bisulfite conversion has long been the gold standard for detection of m(5)C in DNA but it can also be applied to RNA. Here, we detail methods for bisulfite treatment of RNA, locus-specific PCR amplification and detection of candidate sites by sequencing on the Illumina MiSeq platform.

Twitter Demographics

The data shown below were collected from the profiles of 18 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 5%
Unknown 19 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Student > Master 4 20%
Student > Doctoral Student 2 10%
Student > Bachelor 2 10%
Lecturer > Senior Lecturer 1 5%
Other 1 5%
Unknown 6 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 60%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Agricultural and Biological Sciences 1 5%
Unknown 6 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 19 August 2016.
All research outputs
of 9,723,038 outputs
Outputs from Methods in molecular biology
of 7,434 outputs
Outputs of similar age
of 249,962 outputs
Outputs of similar age from Methods in molecular biology
of 348 outputs
Altmetric has tracked 9,723,038 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,434 research outputs from this source. They receive a mean Attention Score of 2.0. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 249,962 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 348 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.