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Transcriptome Data Analysis

Overview of attention for book
Cover of 'Transcriptome Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Comparison of Gene Expression Profiles in Nonmodel Eukaryotic Organisms with RNA-Seq
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    Chapter 2 Microarray Data Analysis for Transcriptome Profiling
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    Chapter 3 Pathway and Network Analysis of Differentially Expressed Genes in Transcriptomes
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    Chapter 4 QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
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    Chapter 5 Tracking Alternatively Spliced Isoforms from Long Reads by SpliceHunter
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    Chapter 6 RNA-Seq-Based Transcript Structure Analysis with TrBorderExt
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    Chapter 7 Analysis of RNA Editing Sites from RNA-Seq Data Using GIREMI
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    Chapter 8 Bioinformatic Analysis of MicroRNA Sequencing Data
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    Chapter 9 Microarray-Based MicroRNA Expression Data Analysis with Bioconductor
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    Chapter 10 Identification and Expression Analysis of Long Intergenic Noncoding RNAs
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    Chapter 11 Analysis of RNA-Seq Data Using TEtranscripts
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    Chapter 12 Computational Analysis of RNA–Protein Interactions via Deep Sequencing
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    Chapter 13 Predicting Gene Expression Noise from Gene Expression Variations
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    Chapter 14 A Protocol for Epigenetic Imprinting Analysis with RNA-Seq Data
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    Chapter 15 Single-Cell Transcriptome Analysis Using SINCERA Pipeline
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    Chapter 16 Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues
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92 tweeters

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Title
Transcriptome Data Analysis
Published by
Humana Press, New York, NY, January 2018
DOI 10.1007/978-1-4939-7710-9
ISBNs
978-1-4939-7709-3, 978-1-4939-7710-9
Editors

Yejun Wang, Ming-an Sun

Twitter Demographics

The data shown below were collected from the profiles of 92 tweeters 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 2%
Student > Master 1 2%
Unknown 41 95%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 5%
Unknown 41 95%