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Patient-Specific Induced Pluripotent Stem Cell Models

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Cover of 'Patient-Specific Induced Pluripotent Stem Cell Models'

Table of Contents

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    Book Overview
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    Chapter 157 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 165 Patient-Specific Induced Pluripotent Stem Cell Models: Characterization of iPS Cell-Derived Cardiomyocytes.
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    Chapter 166 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 167 Modeling Axonal Phenotypes with Human Pluripotent Stem Cells.
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    Chapter 168 In Vitro Modeling of Alcohol-Induced Liver Injury Using Human-Induced Pluripotent Stem Cells.
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    Chapter 169 Modeling Genomic Imprinting Disorders Using Induced Pluripotent Stem Cells.
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    Chapter 170 Generation of Patient-Specific induced Pluripotent Stem Cell from Peripheral Blood Mononuclear Cells by Sendai Reprogramming Vectors.
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    Chapter 171 Using Human Induced Pluripotent Stem Cells to Model Skeletal Diseases
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    Chapter 172 Patient-Specific Induced Pluripotent Stem Cell Models: Generation and Characterization of Cardiac Cells.
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    Chapter 173 Generation of Cardiomyocytes from Pluripotent Stem Cells.
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    Chapter 178 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 179 A Doxycycline-Inducible System for Genetic Correction of iPSC Disease Models.
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    Chapter 194 Multisystemic Disease Modeling of Liver-Derived Protein Folding Disorders Using Induced Pluripotent Stem Cells (iPSCs).
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    Chapter 195 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 196 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 204 Generation of Integration-Free Patient Specific iPS Cells Using Episomal Plasmids Under Feeder Free Conditions.
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    Chapter 205 Generation of Human Induced Pluripotent Stem Cells Using RNA-Based Sendai Virus System and Pluripotency Validation of the Resulting Cell Population.
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    Chapter 225 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 257 Directed Myogenic Differentiation of Human Induced Pluripotent Stem Cells.
  21. Altmetric Badge
    Chapter 258 Generation and Characterization of Induced Pluripotent Stem Cells from Patients with mtDNA Mutations.
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    Chapter 267 Patient-Specific Induced Pluripotent Stem Cell Models
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    Chapter 273 Generation and Characterization of Patient-Specific iPSC Model for Cardiovascular Disease.
  24. Altmetric Badge
    Chapter 278 Transgene-Free Disease-Specific iPSC Generation from Fibroblasts and Peripheral Blood Mononuclear Cells.
Attention for Chapter 169: Modeling Genomic Imprinting Disorders Using Induced Pluripotent Stem Cells.
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Chapter title
Modeling Genomic Imprinting Disorders Using Induced Pluripotent Stem Cells.
Chapter number 169
Book title
Patient-Specific Induced Pluripotent Stem Cell Models
Published in
Methods in molecular biology, December 2014
DOI 10.1007/7651_2014_169
Pubmed ID
Book ISBNs
978-1-4939-3033-3, 978-1-4939-3034-0
Authors

Stormy J Chamberlain, Noelle D Germain, Pin-Fang Chen, Jack S Hsiao, Heather Glatt-Deeley, Stormy J. Chamberlain, Noelle D. Germain, Jack S. Hsiao, Chamberlain, Stormy J., Germain, Noelle D., Chen, Pin-Fang, Hsiao, Jack S., Glatt-Deeley, Heather

Editors

Andras Nagy, Kursad Turksen

Abstract

Induced pluripotent stem cell (iPSC) technology has allowed for the invaluable modeling of many genetic disorders including disorders associated with genomic imprinting. Genomic imprinting involves differential DNA and histone methylation and results in allele-specific gene expression. Most of the epigenetic marks in somatic cells are erased and reestablished during the process of reprogramming into iPSCs. Therefore, in generating models of disorders associated with genomic imprinting, it is important to verify that the imprinting status and allele-specific gene expression patterns of the parental somatic cells are maintained in their derivative iPSCs. Here, we describe three techniques: DNA methylation analysis, allele-specific PCR, and RNA FISH, which we use to analyze genomic imprinting in iPSC models of neurogenetic disorders involving copy number variations of the chromosome 15q11-q13 region.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 32%
Researcher 5 20%
Student > Doctoral Student 3 12%
Student > Bachelor 2 8%
Student > Master 2 8%
Other 2 8%
Unknown 3 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 32%
Agricultural and Biological Sciences 5 20%
Neuroscience 5 20%
Sports and Recreations 1 4%
Psychology 1 4%
Other 2 8%
Unknown 3 12%
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 19 December 2014.
All research outputs
#20,247,117
of 22,775,504 outputs
Outputs from Methods in molecular biology
#9,866
of 13,091 outputs
Outputs of similar age
#296,097
of 353,309 outputs
Outputs of similar age from Methods in molecular biology
#619
of 983 outputs
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We're also able to compare this research output to 983 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.