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miRNomics: MicroRNA Biology and Computational Analysis

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Cover of 'miRNomics: MicroRNA Biology and Computational Analysis'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction to MicroRNAs in Biological Systems
  3. Altmetric Badge
    Chapter 2 The Role of MicroRNAs in Biological Processes
  4. Altmetric Badge
    Chapter 3 The Role of MicroRNAs in Human Diseases
  5. Altmetric Badge
    Chapter 4 Introduction to bioinformatics.
  6. Altmetric Badge
    Chapter 5 MicroRNA and Noncoding RNA-Related Data Sources
  7. Altmetric Badge
    Chapter 6 High-Throughput Approaches for MicroRNA Expression Analysis.
  8. Altmetric Badge
    Chapter 7 Introduction to Machine Learning
  9. Altmetric Badge
    Chapter 8 Introduction to Statistical Methods for MicroRNA Analysis.
  10. Altmetric Badge
    Chapter 9 Computational and Bioinformatics Methods for MicroRNA Gene Prediction
  11. Altmetric Badge
    Chapter 10 Machine Learning Methods for MicroRNA Gene Prediction
  12. Altmetric Badge
    Chapter 11 Functional, Structural, and Sequence Studies of MicroRNA
  13. Altmetric Badge
    Chapter 12 Computational Methods for MicroRNA Target Prediction
  14. Altmetric Badge
    Chapter 13 MicroRNA Target and Gene Validation in Viruses and Bacteria
  15. Altmetric Badge
    Chapter 14 Gene Reporter Assay to Validate MicroRNA Targets in Drosophila S2 Cells.
  16. Altmetric Badge
    Chapter 15 Computational Prediction of MicroRNA Function and Activity
  17. Altmetric Badge
    Chapter 16 Analysis of MicroRNA Expression Using Machine Learning.
  18. Altmetric Badge
    Chapter 17 MicroRNA Expression Landscapes in Stem Cells, Tissues, and Cancer
  19. Altmetric Badge
    Chapter 18 Master Regulators of Posttranscriptional Gene Expression Are Subject to Regulation
  20. Altmetric Badge
    Chapter 19 Use of MicroRNAs in Personalized Medicine
Attention for Chapter 6: High-Throughput Approaches for MicroRNA Expression Analysis.
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Chapter title
High-Throughput Approaches for MicroRNA Expression Analysis.
Chapter number 6
Book title
miRNomics: MicroRNA Biology and Computational Analysis
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-62703-748-8_6
Pubmed ID
Book ISBNs
978-1-62703-747-1, 978-1-62703-748-8
Authors

Bala Gür Dedeoğlu, Dedeoğlu, Bala Gür

Abstract

Profiling microRNA (miRNA) expression is of widespread interest due to their critical roles in diverse biological processes, including development, cell proliferation, differentiation, and apoptosis. Profiling can be achieved via three major methods: amplification-based (real-time quantitative PCR, qRT-PCR), hybridization-based (microarrays), and sequencing-based (next-generation sequencing (NGS)) technologies. The gold standard is qRT-PCR and serves as a platform for single reverse PCR amplification experiments and for a large number of miRNAs in parallel, both by multiplexing and plate based arrays. Currently, qRT-PCR is used for the validation of miRNA profiling results from other platforms. Hybridization based miRNA profiling by microarrays has become a widely used method especially for biomarker and therapeutic target identification. The data obtained from microarrays also enables functional prediction of miRNAs by correlating miRNA expression patterns to corresponding mRNA and protein profiles. Additionally, miRNA profiling strategies based on deep sequencing allow both the identification of novel miRNAs and relative quantification of miRNAs. Each miRNA profiling strategy has specific strengths and challenges that have to be considered depending on the nature of the research context.In this chapter the high-throughput approaches that can be applied to microRNA profiling are discussed starting from small-scale qRT-PCR technology to a wider one, NGS.

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X Demographics

The data shown below were collected from the profiles of 6 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Norway 1 3%
Luxembourg 1 3%
Brazil 1 3%
Unknown 29 88%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 30%
Researcher 9 27%
Student > Ph. D. Student 4 12%
Professor > Associate Professor 2 6%
Student > Doctoral Student 2 6%
Other 4 12%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 42%
Biochemistry, Genetics and Molecular Biology 8 24%
Computer Science 3 9%
Medicine and Dentistry 2 6%
Neuroscience 1 3%
Other 1 3%
Unknown 4 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 December 2013.
All research outputs
#5,975,567
of 22,733,113 outputs
Outputs from Methods in molecular biology
#1,762
of 13,085 outputs
Outputs of similar age
#70,307
of 305,170 outputs
Outputs of similar age from Methods in molecular biology
#75
of 594 outputs
Altmetric has tracked 22,733,113 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 13,085 research outputs from this source. They receive a mean Attention Score of 3.3. 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 305,170 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 76% of its contemporaries.
We're also able to compare this research output to 594 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.