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Next-Generation MicroRNA Expression Profiling Technology

Overview of attention for book
Cover of 'Next-Generation MicroRNA Expression Profiling Technology'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Controlling miRNA Regulation in Disease
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    Chapter 2 Introduction to miRNA Profiling Technologies and Cross-Platform Comparison.
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    Chapter 3 Stem-Loop RT-qPCR for MicroRNA Expression Profiling
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    Chapter 4 Poly(T) adaptor rt-PCR.
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    Chapter 5 MicroRNA In Situ Hybridization
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    Chapter 6 Agilent MicroRNA Microarray Profiling System
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    Chapter 7 miRNA Expression Profiling Using Illumina Universal BeadChips
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    Chapter 8 MicroRNA Expression Analysis Using the Affymetrix Platform.
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    Chapter 9 Individualized miRNA Assay Panels Using Optically Encoded Beads
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    Chapter 10 Microfluidic Primer Extension Assay
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    Chapter 11 MicroRNA Profiling Using µParaflo Microfluidic Array Technology.
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    Chapter 12 MicroRNA Expression Analysis Using the Illumina MicroRNA-Seq Platform.
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    Chapter 13 Next-Generation Sequencing of miRNAs with Roche 454 GS-FLX Technology: Steps for a Successful Application.
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    Chapter 14 Methods for small RNA preparation for digital gene expression profiling by next-generation sequencing.
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    Chapter 15 Profiling of Short RNAs Using Helicos Single-Molecule Sequencing.
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    Chapter 16 deepBase: Annotation and Discovery of MicroRNAs and Other Noncoding RNAs from Deep-Sequencing Data.
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    Chapter 17 PhenomiR: MicroRNAs in Human Diseases and Biological Processes
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    Chapter 18 miRNA Expression Profiling: From Reference Genes to Global Mean Normalization
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    Chapter 19 miRNA Data Analysis: Next-Gen Sequencing.
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    Chapter 20 Integrated miRNA Expression Analysis and Target Prediction.
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    Chapter 21 miRNAs in Human Cancer.
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    Chapter 22 Blood-Based miRNA Preparation for Noninvasive Biomarker Development.
Attention for Chapter 19: miRNA Data Analysis: Next-Gen Sequencing.
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Chapter title
miRNA Data Analysis: Next-Gen Sequencing.
Chapter number 19
Book title
Next-Generation MicroRNA Expression Profiling Technology
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-427-8_19
Pubmed ID
Book ISBNs
978-1-61779-426-1, 978-1-61779-427-8
Authors

Preethi H. Gunaratne, Cristian Coarfa, Benjamin Soibam, Arpit Tandon, Gunaratne, Preethi H., Coarfa, Cristian, Soibam, Benjamin, Tandon, Arpit

Abstract

MicroRNAs (miRNAs) are short, noncoding RNAs that have the capacity to bind, capture, and silence hundreds of genes within and across diverse signaling pathways 1(Bartel, Cell 136:215-33, 2009) Specific sets of miRNAs characterize specific cell lineages of normal organisms and an increasing number of diseases have been shown to be associated with the dysregulation of specific miRNAs. Deep sequencing platforms have revealed unexpected complexity in relation to miRNAs, including 5' and 3'-end-length heterogeneity and RNA editing. These insights not uncovered by previous microarray-based studies underscore the importance of data analysis tools that enable users to rapidly and easily analyze the unprecedented amounts of small RNA sequencing data that is emerging from next-generation sequencing platforms, such as Illumina/Solexa, SOLiD, and 454. In this chapter, we summarize the increasing number of analysis platforms that are available for miRNA discovery and profiling and the identification of functional miRNA-mRNA pairs in the context of biology and disease. We also discuss in greater detail our contributions to this effort.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
Brazil 1 2%
Sweden 1 2%
Belgium 1 2%
China 1 2%
United States 1 2%
Luxembourg 1 2%
Unknown 51 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 33%
Student > Ph. D. Student 11 19%
Student > Master 6 10%
Student > Bachelor 4 7%
Other 4 7%
Other 12 21%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 53%
Biochemistry, Genetics and Molecular Biology 10 17%
Medicine and Dentistry 4 7%
Business, Management and Accounting 2 3%
Computer Science 2 3%
Other 7 12%
Unknown 2 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 December 2011.
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#13,856,164
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Outputs from Methods in molecular biology
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Outputs of similar age from Methods in molecular biology
#288
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