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Disease Gene Identification

Overview of attention for book
Cover of 'Disease Gene Identification'

Table of Contents

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    Book Overview
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    Chapter 1 Identification of Disease Susceptibility Alleles in the Next Generation Sequencing Era
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    Chapter 2 Induced Pluripotent Stem Cells in Disease Modeling and Gene Identification
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    Chapter 3 Development of Targeted Therapies Based on Gene Modification
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    Chapter 4 What Can We Learn About Human Disease from the Nematode C. elegans?
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    Chapter 5 Microbiome Sequencing Methods for Studying Human Diseases
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    Chapter 6 The Emerging Role of Long Noncoding RNAs in Human Disease
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    Chapter 7 Identification of Disease-Related Genes Using a Genome-Wide Association Study Approach
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    Chapter 8 Whole Genome Library Construction for Next Generation Sequencing
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    Chapter 9 Whole Exome Library Construction for Next Generation Sequencing
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    Chapter 10 Optimized Methodology for the Generation of RNA-Sequencing Libraries from Low-Input Starting Material: Enabling Analysis of Specialized Cell Types and Clinical Samples
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    Chapter 11 Using Fluidigm C1 to Generate Single-Cell Full-Length cDNA Libraries for mRNA Sequencing
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    Chapter 12 MiSeq: A Next Generation Sequencing Platform for Genomic Analysis
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    Chapter 13 Methods for CpG Methylation Array Profiling Via Bisulfite Conversion
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    Chapter 14 miRNA Quantification Method Using Quantitative Polymerase Chain Reaction in Conjunction with C q Method
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    Chapter 15 Primary Airway Epithelial Cell Gene Editing Using CRISPR-Cas9
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    Chapter 16 RNA Interference to Knock Down Gene Expression
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    Chapter 17 Using Luciferase Reporter Assays to Identify Functional Variants at Disease-Associated Loci
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    Chapter 18 Physiologic Interpretation of GWAS Signals for Type 2 Diabetes
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    Chapter 19 Identification of Genes for Hereditary Hemochromatosis
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    Chapter 20 Identification of Driver Mutations in Rare Cancers: The Role of SMARCA4 in Small Cell Carcinoma of the Ovary, Hypercalcemic Type (SCCOHT)
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    Chapter 21 The Rise and Fall and Rise of Linkage Analysis as a Technique for Finding and Characterizing Inherited Influences on Disease Expression
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Title
Disease Gene Identification
Published by
Humana Press, New York, NY, March 2018
DOI 10.1007/978-1-4939-7471-9
ISBNs
978-1-4939-7470-2, 978-1-4939-7471-9
Editors

Johanna K. DiStefano

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 21%
Student > Master 4 17%
Student > Ph. D. Student 4 17%
Researcher 3 13%
Student > Doctoral Student 2 8%
Other 1 4%
Unknown 5 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 21%
Pharmacology, Toxicology and Pharmaceutical Science 3 13%
Agricultural and Biological Sciences 3 13%
Immunology and Microbiology 2 8%
Medicine and Dentistry 2 8%
Other 4 17%
Unknown 5 21%