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Muscle Stem Cells

Overview of attention for book
Cover of 'Muscle Stem Cells'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Muscle Stem Cells: A Model System for Adult Stem Cell Biology
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    Chapter 2 Isolation of Muscle Stem Cells from Mouse Skeletal Muscle
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    Chapter 3 Primary Mouse Myoblast Purification using Magnetic Cell Separation
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    Chapter 4 Isolation, Culture, and Immunostaining of Skeletal Muscle Myofibers from Wildtype and Nestin-GFP Mice as a Means to Analyze Satellite Cell
  6. Altmetric Badge
    Chapter 5 Characterization of Drosophila Muscle Stem Cell-Like Adult Muscle Precursors
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    Chapter 6 Using Transgenic Zebrafish to Study Muscle Stem/Progenitor Cells
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    Chapter 7 Muscle Interstitial Cells: A Brief Field Guide to Non-satellite Cell Populations in Skeletal Muscle
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    Chapter 8 Isolation and Characterization of Vessel-Associated Stem/Progenitor Cells from Skeletal Muscle
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    Chapter 9 Fibro/Adipogenic Progenitors (FAPs): Isolation by FACS and Culture
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    Chapter 10 Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells
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    Chapter 11 Engraftment of FACS Isolated Muscle Stem Cells into Injured Skeletal Muscle
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    Chapter 12 Transplantation of Skeletal Muscle Stem Cells
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    Chapter 13 Simultaneous Measurement of Mitochondrial and Glycolytic Activity in Quiescent Muscle Stem Cells
  15. Altmetric Badge
    Chapter 14 Monitoring Autophagy in Muscle Stem Cells
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    Chapter 15 Mimicking Muscle Stem Cell Quiescence in Culture: Methods for Synchronization in Reversible Arrest
  17. Altmetric Badge
    Chapter 16 Methods for Observing and Quantifying Muscle Satellite Cell Motility and Invasion In Vitro
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    Chapter 17 Effects of Macrophage Conditioned-Medium on Murine and Human Muscle Cells: Analysis of Proliferation, Differentiation, and Fusion
  19. Altmetric Badge
    Chapter 18 Optimization of Satellite Cell Culture Through Biomaterials
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    Chapter 19 Systematic Identification of Genes Regulating Muscle Stem Cell Self-Renewal and Differentiation
  21. Altmetric Badge
    Chapter 20 Bioinformatics for Novel Long Intergenic Noncoding RNA (lincRNA) Identification in Skeletal Muscle Cells
Attention for Chapter 10: Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells
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Chapter title
Single Cell Gene Expression Profiling of Skeletal Muscle-Derived Cells
Chapter number 10
Book title
Muscle Stem Cells
Published in
Methods in molecular biology, March 2017
DOI 10.1007/978-1-4939-6771-1_10
Pubmed ID
Book ISBNs
978-1-4939-6769-8, 978-1-4939-6771-1
Authors

Sole Gatto, Pier Lorenzo Puri, Barbora Malecova, Gatto, Sole, Puri, Pier Lorenzo, Malecova, Barbora

Editors

Eusebio Perdiguero, DDW Cornelison

Abstract

Single cell gene expression profiling is a fundamental tool for studying the heterogeneity of a cell population by addressing the phenotypic and functional characteristics of each cell. Technological advances that have coupled microfluidic technologies with high-throughput quantitative RT-PCR analyses have enabled detailed analyses of single cells in various biological contexts. In this chapter, we describe the procedure for isolating the skeletal muscle interstitial cells termed Fibro-Adipogenic Progenitors (FAPs ) and their gene expression profiling at the single cell level. Moreover, we accompany our bench protocol with bioinformatics analysis designed to process raw data as well as to visualize single cell gene expression data. Single cell gene expression profiling is therefore a useful tool in the investigation of FAPs heterogeneity and their contribution to muscle homeostasis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 18%
Lecturer > Senior Lecturer 1 9%
Student > Doctoral Student 1 9%
Student > Ph. D. Student 1 9%
Student > Bachelor 1 9%
Other 2 18%
Unknown 3 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 36%
Chemical Engineering 1 9%
Medicine and Dentistry 1 9%
Engineering 1 9%
Unknown 4 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 14 April 2017.
All research outputs
#18,536,772
of 22,958,253 outputs
Outputs from Methods in molecular biology
#7,935
of 13,137 outputs
Outputs of similar age
#237,978
of 311,244 outputs
Outputs of similar age from Methods in molecular biology
#157
of 268 outputs
Altmetric has tracked 22,958,253 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,137 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 268 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.