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Next-Generation MicroRNA Expression Profiling Technology

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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.
  16. Altmetric Badge
    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.
  18. Altmetric Badge
    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.
  23. Altmetric Badge
    Chapter 22 Blood-Based miRNA Preparation for Noninvasive Biomarker Development.
Attention for Chapter 15: Profiling of Short RNAs Using Helicos Single-Molecule Sequencing.
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Chapter title
Profiling of Short RNAs Using Helicos Single-Molecule Sequencing.
Chapter number 15
Book title
Next-Generation MicroRNA Expression Profiling Technology
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-427-8_15
Pubmed ID
Book ISBNs
978-1-61779-426-1, 978-1-61779-427-8
Authors

Philipp Kapranov, Fatih Ozsolak, Patrice M. Milos, Kapranov, Philipp, Ozsolak, Fatih, Milos, Patrice M.

Abstract

The importance of short (<200 nt) RNAs in cell biogenesis has been well documented. These short RNAs include crucial classes of molecules such as transfer RNAs, small nuclear RNA, microRNAs, and many others (reviewed in Storz et al., Annu Rev Biochem 74:199-217, 2005; Ghildiyal and Zamore, Nat Rev Genet 10:94-108, 2009). Furthermore, the realm of functional RNAs that fall within this size range is growing to include less well-characterized RNAs such as short RNAs found at the promoters and 3' termini of genes (Affymetrix ENCODE Transcriptome Project et al., Nature 457:1028-1032, 2009; Davis and Ares, Proc Natl Acad Sci USA 103:3262-3267, 2006; Kapranov et al., Science 316:1484-1488, 2007; Taft et al., Nat Genet 41:572-578, 2009; Kapranov et al., Nature 466:642-646, 2010), short RNAs involved in paramutation (Rassoulzadegan et al., Nature 441:469-474, 2006), and others (reviewed in Kawaji and Hayashizaki, PLoS Genet 4:e22, 2008). Discovery and accurate quantification of these RNA molecules, less than 200 bases in size, is thus an important and also challenging aspect of understanding the full repertoire of cellular and extracellular RNAs. Here, we describe the strategies and procedures we developed to profile short RNA species using single-molecule sequencing (SMS) and the advantages SMS offers.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Germany 1 3%
Italy 1 3%
Unknown 28 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Researcher 9 29%
Student > Postgraduate 3 10%
Professor 2 6%
Professor > Associate Professor 2 6%
Other 2 6%
Unknown 3 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 52%
Biochemistry, Genetics and Molecular Biology 5 16%
Computer Science 1 3%
Medicine and Dentistry 1 3%
Neuroscience 1 3%
Other 0 0%
Unknown 7 23%
Attention Score in Context

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 13 December 2011.
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#18,301,870
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Outputs from Methods in molecular biology
#7,806
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Outputs of similar age from Methods in molecular biology
#325
of 473 outputs
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