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Single-cell RNA-seq reveals lincRNA expression differences in Hela-S3 cells

Overview of attention for article published in Biotechnology Techniques, November 2016
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Title
Single-cell RNA-seq reveals lincRNA expression differences in Hela-S3 cells
Published in
Biotechnology Techniques, November 2016
DOI 10.1007/s10529-016-2260-7
Pubmed ID
Authors

Jie Wang, Bhaskar Roy

Abstract

To characterize transcriptome-wide lincRNAs of Hela-S3 cell line by analyzing RNA sequencing data to provide a foundation for further functional verification and clinical application of cervical carcinoma development. Single-cell RNA sequencing data of 37 Hela-S3 cells were analysed. On average, 511 lincRNAs were expressed in each cell. Comparing the expression difference of the lincRNAs and protein-coding genes, we found that lincRNAs expression displayed more cell specificity than that of protein-coding genes (t-test, P<2.2E-16). In co-expression network analysis, we identified seven modules and one of them was enriched in pathways of mitotic, packaging of telomere ends, and chromosome maintenance. incRNAs are specifically expressed and form a network to perform function at single cell level. Their expression was more specific than that of protein-coding genes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 23%
Researcher 5 19%
Other 2 8%
Student > Bachelor 2 8%
Student > Doctoral Student 2 8%
Other 3 12%
Unknown 6 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 35%
Agricultural and Biological Sciences 4 15%
Medicine and Dentistry 2 8%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Arts and Humanities 1 4%
Other 2 8%
Unknown 7 27%
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 24 November 2016.
All research outputs
#22,760,732
of 25,377,790 outputs
Outputs from Biotechnology Techniques
#2,492
of 2,762 outputs
Outputs of similar age
#355,119
of 415,192 outputs
Outputs of similar age from Biotechnology Techniques
#12
of 14 outputs
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