Literature DB >> 28968725

A brief review of single-cell transcriptomic technologies.

Tomer Kalisky, Sarit Oriel, Tali Hana Bar-Lev, Nissim Ben-Haim, Ariel Trink, Yishay Wineberg, Itamar Kanter, Shlomit Gilad, Saumyadipta Pyne.   

Abstract

In recent years, there has been an effort to develop new technologies for measuring gene expression and sequence information from thousands of individual cells. Large data sets that were obtained using these 'single cell' technologies have allowed scientists to address fundamental questions in biomedicine ranging from stems cells and development to cancer and immunology. Here, we provide a brief review of recent developments in single-cell technology. Our intention is to provide a quick background for newcomers to the field as well as a deeper description of some of the leading technologies to date.
© The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  RNA sequencing; genomics; single-cell technologies

Mesh:

Substances:

Year:  2018        PMID: 28968725     DOI: 10.1093/bfgp/elx019

Source DB:  PubMed          Journal:  Brief Funct Genomics        ISSN: 2041-2649            Impact factor:   4.241


  16 in total

1.  A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations.

Authors:  Mikael N E Sommarin; Rebecca Warfvinge; Fatemeh Safi; Göran Karlsson
Journal:  J Vis Exp       Date:  2018-10-25       Impact factor: 1.355

Review 2.  Single-Cell RNA Sequencing: A New Window into Cell Scale Dynamics.

Authors:  Sabyasachi Dasgupta; Gary D Bader; Sidhartha Goyal
Journal:  Biophys J       Date:  2018-07-11       Impact factor: 4.033

Review 3.  Tumour heterogeneity and metastasis at single-cell resolution.

Authors:  Devon A Lawson; Kai Kessenbrock; Ryan T Davis; Nicholas Pervolarakis; Zena Werb
Journal:  Nat Cell Biol       Date:  2018-11-26       Impact factor: 28.824

Review 4.  Single-Cell Genomic Analysis in Plants.

Authors:  Yuxuan Yuan; HueyTyng Lee; Haifei Hu; Armin Scheben; David Edwards
Journal:  Genes (Basel)       Date:  2018-01-22       Impact factor: 4.096

Review 5.  Platforms for Single-Cell Collection and Analysis.

Authors:  Lukas Valihrach; Peter Androvic; Mikael Kubista
Journal:  Int J Mol Sci       Date:  2018-03-11       Impact factor: 5.923

Review 6.  Vascular Homeostasis and Inflammation in Health and Disease-Lessons from Single Cell Technologies.

Authors:  Olga Bondareva; Bilal N Sheikh
Journal:  Int J Mol Sci       Date:  2020-06-30       Impact factor: 5.923

7.  AutoImpute: Autoencoder based imputation of single-cell RNA-seq data.

Authors:  Divyanshu Talwar; Aanchal Mongia; Debarka Sengupta; Angshul Majumdar
Journal:  Sci Rep       Date:  2018-11-05       Impact factor: 4.379

8.  Accurate estimation of cell-type composition from gene expression data.

Authors:  Daphne Tsoucas; Rui Dong; Haide Chen; Qian Zhu; Guoji Guo; Guo-Cheng Yuan
Journal:  Nat Commun       Date:  2019-07-05       Impact factor: 14.919

Review 9.  Next-generation sequencing and prenatal 'omics: advanced diagnostics and new insights into human development.

Authors:  Neeta L Vora; Lisa Hui
Journal:  Genet Med       Date:  2018-07-22       Impact factor: 8.822

10.  SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data.

Authors:  Jing Qi; Yang Zhou; Zicen Zhao; Shuilin Jin
Journal:  PLoS Comput Biol       Date:  2021-06-17       Impact factor: 4.475

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