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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
  23. Altmetric Badge
    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 24: Analysis of Alternative Splicing Events in Custom Gene Datasets by AStalavista.
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  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Chapter title
Analysis of Alternative Splicing Events in Custom Gene Datasets by AStalavista.
Chapter number 24
Book title
RNA Bioinformatics
Published in
Methods in molecular biology, December 2014
DOI 10.1007/978-1-4939-2291-8_24
Pubmed ID
Book ISBNs
978-1-4939-2290-1, 978-1-4939-2291-8
Authors

Sylvain Foissac, Michael Sammeth

Editors

Ernesto Picardi

Abstract

Alternative splicing (AS) is a eukaryotic principle to derive more than one RNA product from transcribed genes by removing distinct subsets of introns from a premature polymer. We know today that this process is highly regulated and makes up a large part of the differences between species, cell types, and states. The key to compare AS across different genes or organisms is to tokenize the AS phenomenon into atomary units, so-called AS events. These events then usually are grouped by common patterns to investigate the underlying molecular mechanisms that drive their regulation. However, attempts to decompose loci with AS observations into events are often hampered by applying a limited set of a priori defined event patterns which are not capable to describe all AS configurations and therefore cannot decompose the phenomenon exhaustively.In this chapter, we describe working scenarios of AStalavista, a computational method that reports all AS events reflected by transcript annotations. We show how to practically employ AStalavista to study AS variation in complex transcriptomes, as characterized by the human GENCODE annotation. Our examples demonstrate how the inherent and universal AStalavista paradigm allows for an automatic delineation of AS events in custom gene datasets. Additionally, we sketch an example of an AStalavista use case including next-generation sequencing data (RNA-Seq) to enrich the landscape of discovered AS events.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 44%
Researcher 10 29%
Student > Master 3 9%
Student > Doctoral Student 2 6%
Lecturer > Senior Lecturer 1 3%
Other 2 6%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 62%
Biochemistry, Genetics and Molecular Biology 9 26%
Computer Science 2 6%
Medicine and Dentistry 1 3%
Unknown 1 3%
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.