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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
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    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 21: miRNAs in Human Cancer.
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Chapter title
miRNAs in Human Cancer.
Chapter number 21
Book title
Next-Generation MicroRNA Expression Profiling Technology
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-427-8_21
Pubmed ID
Book ISBNs
978-1-61779-426-1, 978-1-61779-427-8
Authors

Zhong X, Coukos G, Zhang L, Xiaomin Zhong, George Coukos, Lin Zhang, Zhong, Xiaomin, Coukos, George, Zhang, Lin

Abstract

MicroRNAs (miRNAs) are small (∼18-25 nucleotides), endogenous, noncoding RNAs that regulate gene expression in a sequence-specific manner via the degradation of target mRNAs or the inhibition of protein translation. miRNAs are predicted to target up to one-third of all human mRNAs. Each miRNA can target hundreds of transcripts and proteins directly or indirectly, and more than one miRNA can converge on a single target transcript; thus, the potential regulatory circuitry afforded by miRNAs is enormous. Increasing evidence is revealing that the expression of miRNAs is deregulated in cancer. High-throughput miRNA quantification technologies provide powerful tools to study global miRNA profiles. It has become progressively more apparent that, although the number of miRNAs (∼1,000) is much smaller than the number of protein-coding genes (∼22,000), miRNA expression signatures more accurately reflect the developmental lineage and tissue origin of human cancers. Large-scale studies in human cancer have further demonstrated that miRNA expression signatures are associated not only with specific tumor subtypes but also with clinical outcomes.

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 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
United States 2 2%
Italy 1 <1%
Colombia 1 <1%
Canada 1 <1%
India 1 <1%
Unknown 120 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 21%
Researcher 24 19%
Student > Bachelor 18 14%
Student > Master 14 11%
Other 7 5%
Other 21 16%
Unknown 17 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 26%
Medicine and Dentistry 30 23%
Biochemistry, Genetics and Molecular Biology 29 23%
Chemistry 3 2%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 11 9%
Unknown 20 16%

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 11 December 2011.
All research outputs
#13,851,066
of 17,360,236 outputs
Outputs from Methods in molecular biology
#5,044
of 9,915 outputs
Outputs of similar age
#168,012
of 222,009 outputs
Outputs of similar age from Methods in molecular biology
#289
of 467 outputs
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We're also able to compare this research output to 467 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.