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Gene Expression Analysis

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Cover of 'Gene Expression Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Overview of Gene Expression Analysis: Transcriptomics
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    Chapter 2 RNA-Seq and Expression Arrays: Selection Guidelines for Genome-Wide Expression Profiling
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    Chapter 3 A Guide for Designing and Analyzing RNA-Seq Data
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    Chapter 4 SureSelect XT RNA Direct: A Technique for Expression Analysis Through Sequencing of Target-Enriched FFPE Total RNA
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    Chapter 5 Simultaneous, Multiplexed Detection of RNA and Protein on the NanoString ® nCounter ® Platform
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    Chapter 6 Transcript Profiling Using Long-Read Sequencing Technologies
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    Chapter 7 Making and Sequencing Heavily Multiplexed, High-Throughput 16S Ribosomal RNA Gene Amplicon Libraries Using a Flexible, Two-Stage PCR Protocol
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    Chapter 8 MicroRNA Expression Analysis: Next-Generation Sequencing
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    Chapter 9 Identification of Transcriptional Regulators That Bind to Long Noncoding RNAs by RNA Pull-Down and RNA Immunoprecipitation
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    Chapter 10 Single-Cell mRNA-Seq Using the Fluidigm C1 System and Integrated Fluidics Circuits
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    Chapter 11 Current and Future Methods for mRNA Analysis: A Drive Toward Single Molecule Sequencing
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    Chapter 12 Expression Profiling of Differentially Regulated Genes in Fanconi Anemia
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    Chapter 13 A Review of Transcriptome Analysis in Pulmonary Vascular Diseases
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    Chapter 14 Differential Gene Expression Analysis of Plants
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    Chapter 15 High Throughput Sequencing-Based Approaches for Gene Expression Analysis
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    Chapter 16 Network Analysis of Gene Expression
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    Chapter 17 Analysis of ChIP-Seq and RNA-Seq Data with BioWardrobe
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    Chapter 18 Bayesian Network to Infer Drug-Induced Apoptosis Circuits from Connectivity Map Data
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    Chapter 19 Erratum to: RNA-Seq and Expression Arrays: Selection Guidelines for Genome-Wide Expression Profiling
Attention for Chapter 14: Differential Gene Expression Analysis of Plants
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Chapter title
Differential Gene Expression Analysis of Plants
Chapter number 14
Book title
Gene Expression Analysis
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7834-2_14
Pubmed ID
Book ISBNs
978-1-4939-7833-5, 978-1-4939-7834-2
Authors

Mark Arick, Chuan-Yu Hsu, Arick, Mark, Hsu, Chuan-Yu

Abstract

Since the next-generation sequencing (NGS) systems were invented and introduced to life science research about a decade ago, the NGS technology has extensively utilized in wide range of genomic, transcriptomic, and evolutionary studies. Compared with other eukaryotic species, the application of NGS technology in plant research reveals some challenges in sample preparation and data analysis due to some structural and physiological characteristics and genome complexity nature in plants. Hence, despite of the standard sample preparation and data process protocols widely used in high throughput transcriptomic analysis, we also describe the modified hot borate RNA extraction protocol specific for high quality and quantity plant total RNA isolation, and some comments and suggestions to achieve better assessments in the validation of RNA and library quality and data analysis.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 40%
Student > Master 2 13%
Researcher 2 13%
Student > Bachelor 1 7%
Student > Postgraduate 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 40%
Biochemistry, Genetics and Molecular Biology 5 33%
Unknown 4 27%
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 17 May 2018.
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#15,514,052
of 23,056,273 outputs
Outputs from Methods in molecular biology
#5,402
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Outputs of similar age
#269,948
of 442,477 outputs
Outputs of similar age from Methods in molecular biology
#597
of 1,499 outputs
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