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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
  3. Altmetric Badge
    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
  5. Altmetric Badge
    Chapter 4 De Novo Secondary Structure Motif Discovery Using RNAProfile
  6. Altmetric Badge
    Chapter 5 Drawing and Editing the Secondary Structure(s) of RNA
  7. Altmetric Badge
    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
  15. Altmetric Badge
    Chapter 14 Using Deep Sequencing Data for Identification of Editing Sites in Mature miRNAs
  16. Altmetric Badge
    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.
  18. Altmetric Badge
    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.
  21. Altmetric Badge
    Chapter 20 Exploring the RNA Editing Potential of RNA-Seq Data by ExpEdit
  22. Altmetric Badge
    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 11: Transcriptome Assembly and Alternative Splicing Analysis
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About this Attention Score

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

Mentioned by

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1 blog

Citations

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13 Dimensions

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14 Mendeley
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Chapter title
Transcriptome Assembly and Alternative Splicing Analysis
Chapter number 11
Book title
RNA Bioinformatics
Published in
Methods in molecular biology, December 2014
DOI 10.1007/978-1-4939-2291-8_11
Pubmed ID
Book ISBNs
978-1-4939-2290-1, 978-1-4939-2291-8
Authors

Paola Bonizzoni, Gianluca Della Vedova, Graziano Pesole, Ernesto Picardi, Yuri Pirola, Raffaella Rizzi

Editors

Ernesto Picardi

Abstract

Alternative Splicing (AS) is the molecular phenomenon whereby multiple transcripts are produced from the same gene locus. As a consequence, it is responsible for the expansion of eukaryotic transcriptomes. Aberrant AS is involved in the onset and progression of several human diseases. Therefore, the characterization of exon-intron structure of a gene and the detection of corresponding transcript isoforms is an extremely relevant biological task. Nonetheless, the computational prediction of AS events and the repertoire of alternative transcripts is yet a challenging issue.Hereafter we introduce PIntron, a software package to predict the exon-intron structure and the full-length isoforms of a gene given a genomic region and a set of transcripts (ESTs and/or mRNAs). The software is open source and available at http://pintron.algolab.eu . PIntron has been designed for (and extensively tested on) a standard workstation without requiring dedicated expensive hardware. It easily manages large genomic regions and more than 20,000 ESTs, achieving good accuracy as shown in an experimental evaluation performed on 112 well-annotated genes selected from the ENCODE human regions used as training set in the EGASP competition.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 50%
Researcher 3 21%
Student > Bachelor 1 7%
Professor 1 7%
Unknown 2 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 36%
Biochemistry, Genetics and Molecular Biology 4 29%
Computer Science 2 14%
Medicine and Dentistry 1 7%
Unknown 2 14%
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
#76,960
of 354,395 outputs
Outputs of similar age from Methods in molecular biology
#117
of 969 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 354,395 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 969 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.