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Promoter Associated RNA

Overview of attention for book
Cover of 'Promoter Associated RNA'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 ChIP-seq for the Identification of Functional Elements in the Human Genome
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    Chapter 2 Identification of Candidate Functional Elements in the Genome from ChIP-seq Data
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    Chapter 3 GRO-seq, A Tool for Identification of Transcripts Regulating Gene Expression
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    Chapter 4 NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
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    Chapter 5 Deep Cap Analysis of Gene Expression (CAGE): Genome-Wide Identification of Promoters, Quantification of Their Activity, and Transcriptional Network Inference
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    Chapter 6 Deep-RACE: Comprehensive Search for Novel ncRNAs Associated to a Specific Locus
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    Chapter 7 In Silico Prediction of RNA Secondary Structure
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    Chapter 8 Computational Prediction of RNA-Protein Interactions
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    Chapter 9 Isolation of Nuclear RNA-Associated Protein Complexes
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    Chapter 10 Identification of Long Noncoding RNAs Associated to Human Disease Susceptibility
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    Chapter 11 Targeting Promoter-Associated RNAs by siRNAs
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    Chapter 12 RNA-FISH to Study Regulatory RNA at the Site of Transcription
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    Chapter 13 Detection and Characterization of R Loop Structures
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    Chapter 14 Induction of Transcriptional Gene Silencing by Expression of shRNA Directed to c-Myc P2 Promoter in Hepatocellular Carcinoma by Tissue-Specific Virosomal Delivery
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    Chapter 15 Targeting Promoter-Associated Noncoding RNA In Vivo
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    Chapter 16 Manipulation of Promoter-Associated Noncoding RNAs in Mouse Early Embryos for Controlling Sequence-Specific Epigenetic Status
  18. Altmetric Badge
    Chapter 17 Erratum to: NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
Attention for Chapter 8: Computational Prediction of RNA-Protein Interactions
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  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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Chapter title
Computational Prediction of RNA-Protein Interactions
Chapter number 8
Book title
Promoter Associated RNA
Published in
Methods in molecular biology, March 2017
DOI 10.1007/978-1-4939-6716-2_8
Pubmed ID
28349426
Book ISBNs
978-1-4939-6714-8, 978-1-4939-6716-2
Authors

Mann, Carla M., Muppirala, Usha K., Dobbs, Drena, Carla M. Mann, Usha K. Muppirala, Drena Dobbs

Editors

Sara Napoli

Abstract

Experimental methods for identifying protein(s) bound by a specific promoter-associated RNA (paRNA) of interest can be expensive, difficult, and time-consuming. This chapter describes a general computational framework for identifying potential binding partners in RNA-protein complexes or RNA-protein interaction networks. Protocols for using three web-based tools to predict RNA-protein interaction partners are outlined. Also, tables listing additional webservers and software tools for predicting RNA-protein interactions, as well as databases that contain valuable information about known RNA-protein complexes and recognition sites for RNA-binding proteins, are provided. Although only one of the tools described, lncPro, was designed expressly to identify proteins that bind long noncoding RNAs (including paRNAs), all three approaches can be applied to predict potential binding partners for both coding and noncoding RNAs (ncRNAs).

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 32%
Researcher 10 23%
Student > Postgraduate 4 9%
Professor 3 7%
Other 3 7%
Other 7 16%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 39%
Biochemistry, Genetics and Molecular Biology 12 27%
Computer Science 4 9%
Chemistry 3 7%
Medicine and Dentistry 3 7%
Other 3 7%
Unknown 2 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 April 2017.
All research outputs
#14,276,970
of 22,962,258 outputs
Outputs from Methods in molecular biology
#4,160
of 13,136 outputs
Outputs of similar age
#171,870
of 308,511 outputs
Outputs of similar age from Methods in molecular biology
#75
of 303 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,136 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 67% 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 308,511 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 303 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.

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