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

Biotechnology Letters ◽

10.1007/s10529-016-2260-7 ◽

2016 ◽

Vol 39 (3) ◽

pp. 359-366 ◽

Author(s):

Jie Wang ◽

Bhaskar Roy

Keyword(s):

Single Cell ◽

Rna Seq ◽

Hela S3 ◽

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Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells

GigaScience ◽

10.1186/s13742-015-0091-4 ◽

2015 ◽

Vol 4 (1) ◽

Author(s):

Liang Wu ◽

Xiaolong Zhang ◽

Zhikun Zhao ◽

Ling Wang ◽

Bo Li ◽

...

Keyword(s):

Single Cell ◽

Human Cancer ◽

Full Length ◽

Rna Seq ◽

Hela S3 ◽

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Dominant Isoform in Alternative Splicing in HeLa S3 Cell Line Revealed by Single-cell RNA-seq

Proceedings of the 7th International Conference on Computational Systems-Biology and Bioinformatics - CSBio '16 ◽

10.1145/3029375.3029376 ◽

2016 ◽

Author(s):

Zhikun Zhao ◽

Jing Tu ◽

Zuhong Lu ◽

Shiping Liu

Keyword(s):

Alternative Splicing ◽

Single Cell ◽

Cell Line ◽

Rna Seq ◽

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ECBN: Ensemble Clustering based on Bayesian Network inference for Single-cell RNA-seq Data

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9188589 ◽

2020 ◽

Author(s):

Dexin Zhang ◽

Yuan Zhu

Keyword(s):

Bayesian Network ◽

Single Cell ◽

Network Inference ◽

Ensemble Clustering ◽

Rna Seq ◽

Bayesian Network Inference

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Effects of DNA synthesis inhibitors on the induction of hCG subunits and alkaline phosphatase in HeLa S3 cells

10.31274/rtd-180816-5182 ◽

1981 ◽

Author(s):

Kyung-Hea Cho Park

Keyword(s):

Alkaline Phosphatase ◽

Dna Synthesis ◽

Hela S3 ◽

Dna Synthesis Inhibitors ◽

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Faculty Opinions recommendation of Single-cell RNA-seq reveals dynamic paracrine control of cellular variation.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718445581.793514072 ◽

2016 ◽

Author(s):

Cole Trapnell ◽

Serena Liu

Keyword(s):

Single Cell ◽

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Faculty Opinions recommendation of Single-cell RNA-seq identifies a PD-1hi ILC progenitor and defines its development pathway.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726853812.793538588 ◽

2017 ◽

Author(s):

Michael J Holtzman

Keyword(s):

Single Cell ◽

Rna Seq ◽

Development Pathway

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Faculty Opinions recommendation of SCnorm: robust normalization of single-cell RNA-seq data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.727515021.793534656 ◽

2017 ◽

Author(s):

Lauren McIntyre

Keyword(s):

Single Cell ◽

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Faculty Opinions recommendation of Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.727539520.793534943 ◽

2017 ◽

Author(s):

Philippe Saas ◽

Sylvain Perruche

Keyword(s):

Dendritic Cells ◽

Single Cell ◽

Human Blood ◽

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Faculty Opinions recommendation of Detecting Activated Cell Populations Using Single-Cell RNA-Seq.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.731978868.793538401 ◽

2017 ◽

Author(s):

Yi Eve Sun ◽

Weihong Ge

Keyword(s):

Single Cell ◽

Cell Populations ◽

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Faculty Opinions recommendation of Challenges in unsupervised clustering of single-cell RNA-seq data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.734773782.793581119 ◽

2020 ◽

Author(s):

Sushmita Roy

Keyword(s):

Single Cell ◽

Unsupervised Clustering ◽

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