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Single Cell Biomedicine

Overview of attention for book
Cover of 'Single Cell Biomedicine'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Can the Single Cell Make Biomedicine Different?
  3. Altmetric Badge
    Chapter 2 Automated Single-Cell Analysis and Isolation System: A Paradigm Shift in Cell Screening Methods for Bio-medicines
  4. Altmetric Badge
    Chapter 3 Single-Cell Non-coding RNA in Embryonic Development
  5. Altmetric Badge
    Chapter 4 High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications
  6. Altmetric Badge
    Chapter 5 Circulating Tumor Cells: The Importance of Single Cell Analysis
  7. Altmetric Badge
    Chapter 6 Super-Resolution Fluorescence Microscopy for Single Cell Imaging
  8. Altmetric Badge
    Chapter 7 Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis
  9. Altmetric Badge
    Chapter 8 Therapeutic Antibody Discovery in Infectious Diseases Using Single-Cell Analysis
  10. Altmetric Badge
    Chapter 9 Single Cell Genetics and Epigenetics in Early Embryo: From Oocyte to Blastocyst
  11. Altmetric Badge
    Chapter 10 The Potential Roles and Advantages of Single Cell Sequencing in the Diagnosis and Treatment of Hematological Malignancies
  12. Altmetric Badge
    Chapter 11 Application of Single Cell Sequencing in Cancer
  13. Altmetric Badge
    Chapter 12 Emergence of Bias During the Synthesis and Amplification of cDNA for scRNA-seq
  14. Altmetric Badge
    Chapter 13 Detection and Application of RNA Editing in Cancer
  15. Altmetric Badge
    Chapter 14 Is Pooled CRISPR-Screening the Dawn of a New Era for Functional Genomics
  16. Altmetric Badge
    Chapter 15 Roles of Single Cell Systems Biomedicine in Lung Diseases
  17. Altmetric Badge
    Chapter 16 The Significance of Single-Cell Biomedicine in Stem Cells
Attention for Chapter 4: High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications
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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 (84th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

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Citations

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Chapter title
High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications
Chapter number 4
Book title
Single Cell Biomedicine
Published in
Advances in experimental medicine and biology, January 2018
DOI 10.1007/978-981-13-0502-3_4
Pubmed ID
Book ISBNs
978-9-81-130501-6, 978-9-81-130502-3
Authors

Xiaoyun Huang, Shiping Liu, Liang Wu, Miaomiao Jiang, Yong Hou, Huang, Xiaoyun, Liu, Shiping, Wu, Liang, Jiang, Miaomiao, Hou, Yong

Abstract

Single cell sequencing (SCS) can be harnessed to acquire the genomes, transcriptomes and epigenomes from individual cells. Next generation sequencing (NGS) technology is the driving force for single cell sequencing. scRNA-seq requires a lengthy pipeline comprising of single cell sorting, RNA extraction, reverse transcription, amplification, library construction, sequencing and subsequent bioinformatic analysis. Computational algorithms are essential to fulfill many tasks of interest using scRNA-seq data. scRNA-seq has already enabled researchers to revisit long-standing questions in cancer biology, including cancer metastasis, heterogeneity and evolution. Circulating Tumor Cells (CTC) are not only an important mechanism for cancer metastasis, but also provide a possibility to diagnose and monitor cancer in a convenient way independent of surgical resection of the cancer.

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 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 16%
Student > Ph. D. Student 9 12%
Student > Master 5 7%
Student > Bachelor 4 5%
Professor 4 5%
Other 9 12%
Unknown 30 41%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 23%
Agricultural and Biological Sciences 7 10%
Immunology and Microbiology 5 7%
Medicine and Dentistry 5 7%
Chemistry 2 3%
Other 7 10%
Unknown 30 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 20 December 2021.
All research outputs
#2,806,509
of 22,721,584 outputs
Outputs from Advances in experimental medicine and biology
#432
of 4,921 outputs
Outputs of similar age
#66,224
of 440,676 outputs
Outputs of similar age from Advances in experimental medicine and biology
#12
of 237 outputs
Altmetric has tracked 22,721,584 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,921 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done particularly well, scoring higher than 91% 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 440,676 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 84% of its contemporaries.
We're also able to compare this research output to 237 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 94% of its contemporaries.