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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
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    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
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    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
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    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
  20. Altmetric Badge
    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 20: Bioinformatics for Novel Long Intergenic Noncoding RNA (lincRNA) Identification in Skeletal Muscle Cells
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
2 blogs
twitter
1 tweeter

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
13 Mendeley
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Chapter title
Bioinformatics for Novel Long Intergenic Noncoding RNA (lincRNA) Identification in Skeletal Muscle Cells
Chapter number 20
Book title
Muscle Stem Cells
Published in
Methods in molecular biology, March 2017
DOI 10.1007/978-1-4939-6771-1_20
Pubmed ID
Book ISBNs
978-1-4939-6769-8, 978-1-4939-6771-1
Authors

Xianlu Peng, Kun Sun, Jiajian Zhou, Hao Sun, Huating Wang, Peng, Xianlu, Sun, Kun, Zhou, Jiajian, Sun, Hao, Wang, Huating

Editors

Eusebio Perdiguero, DDW Cornelison

Abstract

Long intergenic noncoding RNAs (lincRNAs) have emerged as critical participators in gene regulation in myriads of cell types. The development of the whole transcriptome sequencing technology, or RNA-seq , has enabled novel lincRNA detection, but the bioinformatics analysis toward distinguishing reliable ones remains a challenge. Here, we describe the bioinformatics workflow developed for identifying novel lincRNAs step by step, including read alignment, transcriptome assembly and transcript filtering.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Greece 1 8%
Unknown 12 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 23%
Other 2 15%
Student > Ph. D. Student 2 15%
Lecturer > Senior Lecturer 1 8%
Student > Doctoral Student 1 8%
Other 4 31%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 38%
Biochemistry, Genetics and Molecular Biology 4 31%
Computer Science 2 15%
Immunology and Microbiology 1 8%
Neuroscience 1 8%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 03 March 2017.
All research outputs
#2,050,793
of 21,175,128 outputs
Outputs from Methods in molecular biology
#336
of 11,953 outputs
Outputs of similar age
#41,271
of 276,359 outputs
Outputs of similar age from Methods in molecular biology
#1
of 21 outputs
Altmetric has tracked 21,175,128 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,953 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 97% of its peers.
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 276,359 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.