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Disease Gene Identification

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

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    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)
  22. Altmetric Badge
    Chapter 21 The Rise and Fall and Rise of Linkage Analysis as a Technique for Finding and Characterizing Inherited Influences on Disease Expression
Attention for Chapter 2: Induced Pluripotent Stem Cells in Disease Modeling and Gene Identification
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Chapter title
Induced Pluripotent Stem Cells in Disease Modeling and Gene Identification
Chapter number 2
Book title
Disease Gene Identification
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7471-9_2
Pubmed ID
29423791
Book ISBNs
978-1-4939-7470-2, 978-1-4939-7471-9
Authors

Satish Kumar, John Blangero, Joanne E. Curran, Kumar, Satish, Blangero, John, Curran, Joanne E.

Abstract

Experimental modeling of human inherited disorders provides insight into the cellular and molecular mechanisms involved, and the underlying genetic component influencing, the disease phenotype. The breakthrough development of induced pluripotent stem cell (iPSC) technology represents a quantum leap in experimental modeling of human diseases, providing investigators with a self-renewing and, thus, unlimited source of pluripotent cells for targeted differentiation. In principle, the entire range of cell types found in the human body can be interrogated using an iPSC approach. Therefore, iPSC technology, and the increasingly refined abilities to differentiate iPSCs into disease-relevant target cells, has far-reaching implications for understanding disease pathophysiology, identifying disease-causing genes, and developing more precise therapeutics, including advances in regenerative medicine. In this chapter, we discuss the technological perspectives and recent developments in the application of patient-derived iPSC lines for human disease modeling and disease gene identification.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 21%
Student > Master 10 19%
Student > Ph. D. Student 7 13%
Researcher 3 6%
Professor 2 4%
Other 2 4%
Unknown 18 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 38%
Medicine and Dentistry 6 11%
Agricultural and Biological Sciences 5 9%
Neuroscience 1 2%
Chemistry 1 2%
Other 1 2%
Unknown 19 36%
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 10 February 2018.
All research outputs
#16,045,380
of 23,812,962 outputs
Outputs from Methods in molecular biology
#5,597
of 13,441 outputs
Outputs of similar age
#274,730
of 446,318 outputs
Outputs of similar age from Methods in molecular biology
#594
of 1,481 outputs
Altmetric has tracked 23,812,962 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,441 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 446,318 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,481 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.

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