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RNA Bioinformatics

Overview of attention for book
Cover of 'RNA Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Free Energy Minimization to Predict RNA Secondary Structures and Computational RNA Design
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    Chapter 2 RNA Secondary Structure Prediction from Multi-Aligned Sequences
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    Chapter 3 A Simple Protocol for the Inference of RNA Global Pairwise Alignments
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    Chapter 4 De Novo Secondary Structure Motif Discovery Using RNAProfile
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    Chapter 5 Drawing and Editing the Secondary Structure(s) of RNA
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    Chapter 6 Modeling and Predicting RNA Three-Dimensional Structures
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    Chapter 7 Fast Prediction of RNA–RNA Interaction Using Heuristic Algorithm
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    Chapter 8 Quality Control of RNA-Seq Experiments.
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    Chapter 9 Accurate Mapping of RNA-Seq Data.
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    Chapter 10 Quantifying Entire Transcriptomes by Aligned RNA-Seq Data
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    Chapter 11 Transcriptome Assembly and Alternative Splicing Analysis
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    Chapter 12 Detection of post-transcriptional RNA editing events.
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    Chapter 13 Prediction of miRNA Targets
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    Chapter 14 Using Deep Sequencing Data for Identification of Editing Sites in Mature miRNAs
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    Chapter 15 NGS-Trex: An Automatic Analysis Workflow for RNA-Seq Data
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    Chapter 16 e-DNA Meta-Barcoding: From NGS Raw Data to Taxonomic Profiling.
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    Chapter 17 Deciphering metatranscriptomic data.
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    Chapter 18 RIP-Seq Data Analysis to Determine RNA–Protein Associations
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    Chapter 19 The ViennaRNA Web Services.
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    Chapter 20 Exploring the RNA Editing Potential of RNA-Seq Data by ExpEdit
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    Chapter 21 A Guideline for the Annotation of UTR Regulatory Elements in the UTRsite Collection
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    Chapter 22 Rfam: Annotating Families of Non-Coding RNA Sequences
  24. Altmetric Badge
    Chapter 23 ASPicDB: A Database Web Tool for Alternative Splicing Analysis
  25. Altmetric Badge
    Chapter 24 Analysis of Alternative Splicing Events in Custom Gene Datasets by AStalavista.
  26. Altmetric Badge
    Chapter 25 Computational Design of Artificial RNA Molecules for Gene Regulation
Attention for Chapter 18: RIP-Seq Data Analysis to Determine RNA–Protein Associations
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Citations

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Chapter title
RIP-Seq Data Analysis to Determine RNA–Protein Associations
Chapter number 18
Book title
RNA Bioinformatics
Published in
Methods in molecular biology, December 2014
DOI 10.1007/978-1-4939-2291-8_18
Pubmed ID
Book ISBNs
978-1-4939-2290-1, 978-1-4939-2291-8
Authors

Federico Zambelli, Giulio Pavesi

Editors

Ernesto Picardi

Abstract

Next-generation sequencing (NGS) technologies have opened new avenues of unprecedented power for research in molecular biology and genetics. In particular, their application to the study of RNA-binding proteins (RBPs), extracted through immunoprecipitation (RIP), permits to sequence and characterize all RNAs that were found to be bound in vivo by a given RBP (RIP-Seq). On the other hand, NGS-based experiments, including RIP-Seq, produce millions of short sequence fragments that have to be processed with suitable bioinformatic tools and methods to recover and/or quantify the original sequence sample. In this chapter we provide a survey of different approaches that can be taken for the analysis of RIP-Seq data and the identification of the RNAs bound by a given RBP.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Greece 1 1%
Brazil 1 1%
Unknown 81 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 25%
Student > Ph. D. Student 20 24%
Student > Master 10 12%
Student > Bachelor 5 6%
Professor > Associate Professor 5 6%
Other 10 12%
Unknown 13 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 39%
Agricultural and Biological Sciences 25 30%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Chemistry 2 2%
Immunology and Microbiology 1 1%
Other 4 5%
Unknown 17 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 January 2015.
All research outputs
#5,733,619
of 22,778,347 outputs
Outputs from Methods in molecular biology
#1,605
of 13,093 outputs
Outputs of similar age
#76,939
of 353,320 outputs
Outputs of similar age from Methods in molecular biology
#118
of 983 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 13,093 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 87% 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 353,320 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 78% of its contemporaries.
We're also able to compare this research output to 983 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.