Literature DB >> 26000846

The technology and biology of single-cell RNA sequencing.

Aleksandra A Kolodziejczyk1, Jong Kyoung Kim2, Valentine Svensson2, John C Marioni1, Sarah A Teichmann3.   

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.
Copyright © 2015 Elsevier Inc. All rights reserved.

Mesh:

Year:  2015        PMID: 26000846     DOI: 10.1016/j.molcel.2015.04.005

Source DB:  PubMed          Journal:  Mol Cell        ISSN: 1097-2765            Impact factor:   17.970


  335 in total

1.  SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery.

Authors:  Siwen Hu-Lieskovan; Srabani Bhaumik; Kavita Dhodapkar; Jean-Charles J B Grivel; Sumati Gupta; Brent A Hanks; Sylvia Janetzki; Thomas O Kleen; Yoshinobu Koguchi; Amanda W Lund; Cristina Maccalli; Yolanda D Mahnke; Ruslan D Novosiadly; Senthamil R Selvan; Tasha Sims; Yingdong Zhao; Holden T Maecker
Journal:  J Immunother Cancer       Date:  2020-12       Impact factor: 13.751

Review 2.  Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics.

Authors:  Romain Banchereau; Alma-Martina Cepika; Jacques Banchereau; Virginia Pascual
Journal:  Annu Rev Immunol       Date:  2017-01-30       Impact factor: 28.527

3.  The Use of the Fluidigm C1 for RNA Expression Analyses of Single Cells.

Authors:  Daniel M DeLaughter
Journal:  Curr Protoc Mol Biol       Date:  2018-04

Review 4.  Advances in Transcriptomics: Investigating Cardiovascular Disease at Unprecedented Resolution.

Authors:  Robert C Wirka; Milos Pjanic; Thomas Quertermous
Journal:  Circ Res       Date:  2018-04-27       Impact factor: 17.367

Review 5.  A periodic table of cell types.

Authors:  Bo Xia; Itai Yanai
Journal:  Development       Date:  2019-06-27       Impact factor: 6.868

6.  Single-cell systems biology: probing the basic unit of information flow.

Authors:  Simona Patange; Michelle Girvan; Daniel R Larson
Journal:  Curr Opin Syst Biol       Date:  2017-12-06

7.  Nonparametric expression analysis using inferential replicate counts.

Authors:  Anqi Zhu; Avi Srivastava; Joseph G Ibrahim; Rob Patro; Michael I Love
Journal:  Nucleic Acids Res       Date:  2019-10-10       Impact factor: 16.971

8.  A field guide for the compositional analysis of any-omics data.

Authors:  Thomas P Quinn; Ionas Erb; Greg Gloor; Cedric Notredame; Mark F Richardson; Tamsyn M Crowley
Journal:  Gigascience       Date:  2019-09-01       Impact factor: 6.524

Review 9.  Challenges and unanswered questions for the next decade of circulating tumour cell research in lung cancer.

Authors:  Sumitra Mohan; Francesca Chemi; Ged Brady
Journal:  Transl Lung Cancer Res       Date:  2017-08

Review 10.  RNA-Seq methods for transcriptome analysis.

Authors:  Radmila Hrdlickova; Masoud Toloue; Bin Tian
Journal:  Wiley Interdiscip Rev RNA       Date:  2016-05-19       Impact factor: 9.957

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