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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.
  23. Altmetric Badge
    Chapter 22 Blood-Based miRNA Preparation for Noninvasive Biomarker Development.
Attention for Chapter 16: deepBase: Annotation and Discovery of MicroRNAs and Other Noncoding RNAs from Deep-Sequencing Data.
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Chapter title
deepBase: Annotation and Discovery of MicroRNAs and Other Noncoding RNAs from Deep-Sequencing Data.
Chapter number 16
Book title
Next-Generation MicroRNA Expression Profiling Technology
Published in
Methods in molecular biology, January 2012
DOI 10.1007/978-1-61779-427-8_16
Pubmed ID
Book ISBNs
978-1-61779-426-1, 978-1-61779-427-8
Authors

Jian-Hua Yang, Liang-Hu Qu, Yang, Jian-Hua, Qu, Liang-Hu

Abstract

Recent advances in high-throughput deep-sequencing technology have produced large numbers of short and long RNA sequences and enabled the detection and profiling of known and novel microRNAs (miRNAs) and other noncoding RNAs (ncRNAs) at unprecedented sensitivity and depth. In this chapter, we describe the use of deepBase, a database that we have developed to integrate all public deep-sequencing data and to facilitate the comprehensive annotation and discovery of miRNAs and other ncRNAs from these data. deepBase provides an integrative, interactive, and versatile web graphical interface to evaluate miRBase-annotated miRNA genes and other known ncRNAs, explores the expression patterns of miRNAs and other ncRNAs, and discovers novel miRNAs and other ncRNAs from deep-sequencing data. deepBase also provides a deepView genome browser to comparatively analyze these data at multiple levels. deepBase is available at http://deepbase.sysu.edu.cn/.

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

Geographical breakdown

Country Count As %
Turkey 1 3%
Italy 1 3%
Brazil 1 3%
Canada 1 3%
Japan 1 3%
United States 1 3%
Unknown 25 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 29%
Student > Ph. D. Student 8 26%
Student > Bachelor 3 10%
Student > Master 3 10%
Professor 3 10%
Other 4 13%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 48%
Biochemistry, Genetics and Molecular Biology 6 19%
Computer Science 2 6%
Medicine and Dentistry 2 6%
Neuroscience 2 6%
Other 3 10%
Unknown 1 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 13 December 2011.
All research outputs
#13,856,164
of 17,367,552 outputs
Outputs from Methods in molecular biology
#5,046
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Outputs of similar age
#167,908
of 222,079 outputs
Outputs of similar age from Methods in molecular biology
#288
of 466 outputs
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