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Molecular Cell
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Molecular Cell
Article . 2015
License: Elsevier Non-Commercial
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Molecular Cell
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The Technology and Biology of Single-Cell RNA Sequencing

Authors: Aleksandra A. Kolodziejczyk; Aleksandra A. Kolodziejczyk; Sarah A. Teichmann; Sarah A. Teichmann; John C. Marioni; John C. Marioni; Valentine Svensson; +1 Authors

The Technology and Biology of Single-Cell RNA Sequencing

Abstract

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications.

Keywords

Models, Genetic, Sequence Analysis, RNA, Gene Expression Profiling, Genetic Variation, Cell Biology, Alternative Splicing, Animals, Humans, Cell Lineage, Gene Regulatory Networks, Single-Cell Analysis, Molecular Biology

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
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!
1K
Top 0.01%
Top 1%
Top 0.1%
hybrid