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Single Cell Biomedicine

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

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Can the Single Cell Make Biomedicine Different?
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    Chapter 2 Automated Single-Cell Analysis and Isolation System: A Paradigm Shift in Cell Screening Methods for Bio-medicines
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    Chapter 3 Single-Cell Non-coding RNA in Embryonic Development
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    Chapter 4 High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications
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    Chapter 5 Circulating Tumor Cells: The Importance of Single Cell Analysis
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    Chapter 6 Super-Resolution Fluorescence Microscopy for Single Cell Imaging
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    Chapter 7 Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis
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    Chapter 8 Therapeutic Antibody Discovery in Infectious Diseases Using Single-Cell Analysis
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    Chapter 9 Single Cell Genetics and Epigenetics in Early Embryo: From Oocyte to Blastocyst
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    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
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    Chapter 12 Emergence of Bias During the Synthesis and Amplification of cDNA for scRNA-seq
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    Chapter 13 Detection and Application of RNA Editing in Cancer
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    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
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    Chapter 16 The Significance of Single-Cell Biomedicine in Stem Cells
Attention for Chapter 7: Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis
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Chapter title
Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis
Chapter number 7
Book title
Single Cell Biomedicine
Published in
Advances in experimental medicine and biology, January 2018
DOI 10.1007/978-981-13-0502-3_7
Pubmed ID
Book ISBNs
978-9-81-130501-6, 978-9-81-130502-3
Authors

Zheng Wang, Xiaoju Zhang, Wang, Zheng, Zhang, Xiaoju

Abstract

In the proteomic and genomic era, lung cancer researchers are increasingly under challenge with traditional protein analyzing tools. High output, multiplexed analytical procedures are in demand for disclosing the post-translational modification, molecular interactions and signaling pathways of proteins precisely, specifically, dynamically and systematically, as well as for identifying novel proteins and their functions. This could be better realized by single-cell proteomic methods than conventional proteomic methods. Using single-cell proteomic tools including flow cytometry, mass cytometry, microfluidics and chip technologies, chemical cytometry, single-cell western blotting, the quantity and functions of proteins are analyzed simultaneously. Aside from deciphering disease mechanisms, single-cell proteomic techniques facilitate the identification and screening of biomarkers, molecular targets and promising compounds as well. This review summarized single-cell proteomic tools and their use in lung cancer.

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 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 > Ph. D. Student 3 27%
Researcher 2 18%
Unspecified 1 9%
Professor > Associate Professor 1 9%
Other 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 27%
Agricultural and Biological Sciences 2 18%
Unspecified 1 9%
Chemistry 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 19 December 2018.
All research outputs
#15,538,060
of 23,092,602 outputs
Outputs from Advances in experimental medicine and biology
#2,526
of 4,976 outputs
Outputs of similar age
#270,127
of 442,643 outputs
Outputs of similar age from Advances in experimental medicine and biology
#111
of 237 outputs
Altmetric has tracked 23,092,602 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 4,976 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 37th percentile – i.e., 37% 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 442,643 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 237 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.