Literature DB >> 24292433

High-throughput, multiparameter analysis of single cells.

Thomas Haselgrübler1, Michaela Haider, Bozhi Ji, Kata Juhasz, Alois Sonnleitner, Zsolt Balogi, Jan Hesse.   

Abstract

Heterogeneity of cell populations in various biological systems has been widely recognized, and the highly heterogeneous nature of cancer cells has been emerging with clinical relevance. Single-cell analysis using a combination of high-throughput and multiparameter approaches is capable of reflecting cell-to-cell variability, and at the same time of unraveling the complexity and interdependence of cellular processes in the individual cells of a heterogeneous population. In this review, analytical methods and microfluidic tools commonly used for high-throughput, multiparameter single-cell analysis of DNA, RNA, and proteins are discussed. Applications and limitations of currently available technologies for cancer research and diagnostics are reviewed in the light of the ultimate goal to establish clinically applicable assays.

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Year:  2013        PMID: 24292433     DOI: 10.1007/s00216-013-7485-x

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  10 in total

1.  Single cell studies of mouse embryonic stem cell (mESC) differentiation by electrical impedance measurements in a microfluidic device.

Authors:  Ying Zhou; Srinjan Basu; Ernest Laue; Ashwin A Seshia
Journal:  Biosens Bioelectron       Date:  2016-03-02       Impact factor: 10.618

2.  Tools for Single-Cell Kinetic Analysis of Virus-Host Interactions.

Authors:  Jay W Warrick; Andrea Timm; Adam Swick; John Yin
Journal:  PLoS One       Date:  2016-01-11       Impact factor: 3.240

3.  AirLab: a cloud-based platform to manage and share antibody-based single-cell research.

Authors:  Raúl Catena; Alaz Özcan; Andrea Jacobs; Stephane Chevrier; Bernd Bodenmiller
Journal:  Genome Biol       Date:  2016-06-29       Impact factor: 13.583

4.  SU-8 free-standing microfluidic probes.

Authors:  A A Kim; K Kustanovich; D Baratian; A Ainla; M Shaali; G D M Jeffries; A Jesorka
Journal:  Biomicrofluidics       Date:  2017-02-14       Impact factor: 2.800

5.  Coarse-graining bacteria colonies for modelling critical solute distributions in picolitre bioreactors for bacterial studies on single-cell level.

Authors:  Christoph Westerwalbesloh; Alexander Grünberger; Wolfgang Wiechert; Dietrich Kohlheyer; Eric von Lieres
Journal:  Microb Biotechnol       Date:  2017-04-03       Impact factor: 5.813

6.  Novel computational model of gastrula morphogenesis to identify spatial discriminator genes by self-organizing map (SOM) clustering.

Authors:  Tomoya Mori; Haruka Takaoka; Junko Yamane; Cantas Alev; Wataru Fujibuchi
Journal:  Sci Rep       Date:  2019-08-29       Impact factor: 4.379

Review 7.  From observing to predicting single-cell structure and function with high-throughput/high-content microscopy.

Authors:  Anatole Chessel; Rafael E Carazo Salas
Journal:  Essays Biochem       Date:  2019-07-03       Impact factor: 8.000

8.  Single-cell transcriptomics allows novel insights into aging and circadian processes.

Authors:  Sara S Fonseca Costa; Marc Robinson-Rechavi; Jürgen A Ripperger
Journal:  Brief Funct Genomics       Date:  2020-12-04       Impact factor: 4.241

9.  From imaging a single cell to implementing precision medicine: an exciting new era.

Authors:  Loukia G Karacosta
Journal:  Emerg Top Life Sci       Date:  2021-12-21

Review 10.  Single Cell Isolation and Analysis.

Authors:  Ping Hu; Wenhua Zhang; Hongbo Xin; Glenn Deng
Journal:  Front Cell Dev Biol       Date:  2016-10-25
  10 in total

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