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Selenoproteins

Overview of attention for book
Cover of 'Selenoproteins'

Table of Contents

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    Book Overview
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    Chapter 1 SECISearch3 and Seblastian: In-Silico Tools to Predict SECIS Elements and Selenoproteins
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    Chapter 2 Selenoprofiles: A Computational Pipeline for Annotation of Selenoproteins
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    Chapter 3 SelGenAmic: An Algorithm for Selenoprotein Gene Assembly
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    Chapter 4 Selenocysteine tRNA[Ser]Sec, the Central Component of Selenoprotein Biosynthesis: Isolation, Identification, Modification, and Sequencing
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    Chapter 5 Identification and Characterization of Proteins that Bind to Selenoprotein 3′ UTRs
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    Chapter 6 Specific Chemical Approaches for Studying Mammalian Ribosomes Complexed with Ligands Involved in Selenoprotein Synthesis
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    Chapter 7 In Vitro Translation Assays for Selenocysteine Insertion
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    Chapter 8 Studying Selenoprotein mRNA Translation Using RNA-Seq and Ribosome Profiling
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    Chapter 9 Modification of Selenoprotein mRNAs by Cap Tri-methylation
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    Chapter 10 Total Selenium Quantification in Biological Samples by Inductively Coupled Plasma Mass Spectrometry (ICP-MS)
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    Chapter 11 Quantification of SeMet and SeCys in Biological Fluids and Tissues by Liquid Chromatography Coupled to Inductively Coupled Plasma Mass Spectrometry (HPLC-ICP MS)
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    Chapter 12 Simultaneous Speciation of Selenoproteins and Selenometabolites in Plasma and Serum
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    Chapter 13 Radioactive 75 Se Labeling and Detection of Selenoproteins
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    Chapter 14 Nonradioactive Isotopic Labeling and Tracing of Selenoproteins in Cultured Cell Lines
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    Chapter 15 Detection of Selenoproteins by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP MS) in Immobilized pH Gradient (IPG) Strips
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    Chapter 16 Imaging of Selenium by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) in 2-D Electrophoresis Gels and Biological Tissues
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    Chapter 17 Overexpression of Recombinant Selenoproteins in E. coli
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    Chapter 18 Preparation of Selenocysteine-Containing Forms of Human SELENOK and SELENOS
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    Chapter 19 Selenocysteine-Mediated Expressed Protein Ligation of SELENOM
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    Chapter 20 Monitoring of Methionine Sulfoxide Content and Methionine Sulfoxide Reductase Activity
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    Chapter 21 Selective Evaluation of Thioredoxin Reductase Enzymatic Activities
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    Chapter 22 Association of Single Nucleotide Polymorphisms in Selenoprotein Genes with Cancer Risk
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    Chapter 23 Identification of Genetic Disorders Causing Disruption of Selenoprotein Biosynthesis
Attention for Chapter 8: Studying Selenoprotein mRNA Translation Using RNA-Seq and Ribosome Profiling
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)

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Chapter title
Studying Selenoprotein mRNA Translation Using RNA-Seq and Ribosome Profiling
Chapter number 8
Book title
Selenoproteins
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7258-6_8
Pubmed ID
Book ISBNs
978-1-4939-7257-9, 978-1-4939-7258-6
Authors

Brian K. Dalley, Lisa Baird, Michael T. Howard

Abstract

Deep sequencing of ribosome protected mRNA footprints, also called ribosome profiling or Ribo-Seq, is a relatively new methodology well suited to address questions regarding the mechanisms and efficiency of protein expression. Specifically, the ability of this technique to quantify ribosome abundance with codon resolution enables experiments aimed at studying many aspects of translation, including gene-specific translational efficiency, translation of regulatory upstream short open reading frames, sites of ribosome pausing, and most importantly for selenoproteins, the efficiency by which UGA codons are redefined to encode selenocysteine. Here, we describe a streamlined protocol that was developed in our lab to process mammalian tissue to produce the requisite matched ribosome profiling and RNA-Seq libraries for deep sequencing.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 33%
Other 1 17%
Student > Postgraduate 1 17%
Student > Doctoral Student 1 17%
Unknown 1 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 50%
Agricultural and Biological Sciences 2 33%
Unknown 1 17%

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 12 October 2017.
All research outputs
#6,682,759
of 12,378,936 outputs
Outputs from Methods in molecular biology
#1,847
of 8,316 outputs
Outputs of similar age
#115,759
of 273,631 outputs
Outputs of similar age from Methods in molecular biology
#1
of 1 outputs
Altmetric has tracked 12,378,936 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,316 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 76% 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 273,631 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them