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Translatome profiling: methods for genome-scale analysis of mRNA translation

Overview of attention for article published in Briefings in Functional Genomics, November 2014
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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 (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
4 X users
patent
1 patent
wikipedia
7 Wikipedia pages
googleplus
1 Google+ user
reddit
1 Redditor

Readers on

mendeley
414 Mendeley
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Article details
Title
Translatome profiling: methods for genome-scale analysis of mRNA translation
Published in
Briefings in Functional Genomics, November 2014
DOI 10.1093/bfgp/elu045
Pubmed ID
Authors
Abstract

During the past decade, there has been a rapidly increased appreciation of the role of translation as a key regulatory node in gene expression. Thereby, the development of methods to infer the translatome, which refers to the entirety of mRNAs associated with ribosomes for protein synthesis, has facilitated the discovery of new principles and mechanisms of translation and expanded our view of the underlying logic of protein synthesis. Here, we review the three main methodologies for translatome analysis, and we highlight some of the recent discoveries made using each technique. We first discuss polysomal profiling, a classical technique that involves the separation of mRNAs depending on the number of bound ribosomes using a sucrose gradient, and which has been combined with global analysis tools such as DNA microarrays or high-throughput RNA sequencing to identify the RNAs in polysomal fractions. We then introduce ribosomal profiling, a recently established technique that enables the mapping of ribosomes along mRNAs at near-nucleotide resolution on a global scale. We finally refer to ribosome affinity purification techniques that are based on the cell-type-specific expression of tagged ribosomal proteins, allowing the capture of translatomes from specialized cells in organisms. We discuss the advantages and disadvantages of these three main techniques in the pursuit of defining the translatome, and we speculate about future developments.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 414 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 <1%
Italy 2 <1%
United Kingdom 2 <1%
New Zealand 1 <1%
China 1 <1%
Unknown 406 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 94 23%
Researcher 78 19%
Student > Master 57 14%
Student > Bachelor 34 8%
Student > Doctoral Student 24 6%
Other 44 11%
Unknown 83 20%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 126 30%
Biochemistry, Genetics and Molecular Biology 125 30%
Neuroscience 20 5%
Medicine and Dentistry 9 2%
Computer Science 7 2%
Other 28 7%
Unknown 99 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 22 August 2026.
All research outputs
#4,476,332
of 32,046,026 outputs
Outputs from Briefings in Functional Genomics
#89
of 652 outputs
Outputs of similar age
#43,982
of 296,542 outputs
Outputs of similar age from Briefings in Functional Genomics
#3
of 9 outputs
Altmetric has tracked 32,046,026 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 652 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 86% 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 296,542 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 85% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.