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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
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    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
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    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
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    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 8: Therapeutic Antibody Discovery in Infectious Diseases Using Single-Cell Analysis
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Chapter title
Therapeutic Antibody Discovery in Infectious Diseases Using Single-Cell Analysis
Chapter number 8
Book title
Single Cell Biomedicine
Published in
Advances in experimental medicine and biology, January 2018
DOI 10.1007/978-981-13-0502-3_8
Pubmed ID
29943298
Book ISBNs
978-9-81-130501-6, 978-9-81-130502-3
Authors

Alexandria Voigt, Touyana Semenova, Janet Yamamoto, Veronique Etienne, Cuong Q. Nguyen, Voigt, Alexandria, Semenova, Touyana, Yamamoto, Janet, Etienne, Veronique, Nguyen, Cuong Q.

Abstract

Since the discovery of mouse hybridoma technology by Kohler and Milstein in 1975, significant progress has been made in monoclonal antibody production. Advances in B cell immortalization and phage display technologies have generated a myriad of valuable monoclonal antibodies for diagnosis and treatment. Technological breakthroughs in various fields of 'omics have shed crucial insights into cellular heterogeneity of a biological system in which the functional individuality of a single cell must be considered. Based on this important concept, remarkable discoveries in single-cell analysis have made in identifying and isolating functional B cells that produce beneficial therapeutic monoclonal antibodies. In this review, we will discuss three traditional methods of antibody discovery. Recent technological platforms for single-cell antibody discovery will be reviewed. We will discuss the application of the single-cell analysis in finding therapeutic antibodies for human immunodeficiency virus and emerging Zika arbovirus.

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

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 29%
Student > Ph. D. Student 4 9%
Student > Master 4 9%
Student > Doctoral Student 3 7%
Professor 2 4%
Other 3 7%
Unknown 16 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 13%
Immunology and Microbiology 4 9%
Medicine and Dentistry 3 7%
Agricultural and Biological Sciences 3 7%
Engineering 2 4%
Other 6 13%
Unknown 21 47%
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 27 June 2018.
All research outputs
#18,640,437
of 23,092,602 outputs
Outputs from Advances in experimental medicine and biology
#3,335
of 4,976 outputs
Outputs of similar age
#330,852
of 442,643 outputs
Outputs of similar age from Advances in experimental medicine and biology
#154
of 237 outputs
Altmetric has tracked 23,092,602 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 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 19th percentile – i.e., 19% 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 14th percentile – i.e., 14% 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 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.

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