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Scandinavian Journal of Immunology
Article . 2020 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Scandinavian Journal of Immunology
Article
License: CC BY
Data sources: UnpayWall
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The prospects of single‐cell analysis in autoimmunity

Authors: André Sulen; Shahinul Islam; Anette S. B. Wolff; Bergithe E. Oftedal;

The prospects of single‐cell analysis in autoimmunity

Abstract

AbstractIn the last decade, there has been a tremendous development of technologies focused on analysing various molecular attributes in single cells, with an ever‐increasing number of parameters becoming available at the DNA, RNA and protein levels. Much of this progress has involved cells in suspension, but also in situ analysis of tissues has taken great leaps. Paralleling the development in the laboratory, and because of increasing complexity, the analysis of single‐cell data is also constantly being updated with new algorithms and analysis platforms. Our immune system shares this complexity, and immunologists have therefore been in the forefront of this technological development. These technologies clearly open new avenues for immunology research, maybe particularly within autoimmunity where the interaction between the faulty immune system and the thymus or the target organ is important. However, the technologies currently available can seem overwhelming and daunting. The aim of this review is to remedy this by giving a balanced overview of the prospects of using single‐cell analysis in basal and clinical autoimmunity research, with an emphasis on endocrine autoimmunity.

Keywords

Sequence Analysis, RNA, Gene Expression Profiling, Immune System, Animals, Computational Biology, Humans, Autoimmunity, Single-Cell Analysis, Flow Cytometry, Autoimmune Diseases

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
hybrid