Literature DB >> 23084076

Investigating transcriptional states at single-cell-resolution.

Julia Tischler1, M Azim Surani.   

Abstract

Gene expression analysis at single-cell-resolution is a powerful tool for uncovering individual cell differences within heterogeneous cell populations and complex tissues, which can provide invaluable insights into the extent of gene expression variability. Multi-dimensional information of gene expression at the level of the individual cell can help to identify distinct and rare molecular cell 'states' within populations and aid in unravelling genetic regulatory circuits. Gene expression analysis at the single-cell-level will also enhance our understanding of the molecular basis of aberrant cell states and disease development and holds great promise for the advancement of personalized medicine. We present approaches that provide large-scale views of gene expression at the level of the individual cell.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23084076     DOI: 10.1016/j.copbio.2012.09.013

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  19 in total

Review 1.  The applications of single-cell genomics.

Authors:  Michael Lovett
Journal:  Hum Mol Genet       Date:  2013-08-06       Impact factor: 6.150

2.  Reconstruction of the mouse otocyst and early neuroblast lineage at single-cell resolution.

Authors:  Robert Durruthy-Durruthy; Assaf Gottlieb; Byron H Hartman; Jörg Waldhaus; Roman D Laske; Russ Altman; Stefan Heller
Journal:  Cell       Date:  2014-04-24       Impact factor: 41.582

Review 3.  Single-Cell RNA Sequencing: Unraveling the Brain One Cell at a Time.

Authors:  Dimitry Ofengeim; Nikolaos Giagtzoglou; Dann Huh; Chengyu Zou; Junying Yuan
Journal:  Trends Mol Med       Date:  2017-05-10       Impact factor: 11.951

Review 4.  Single molecule fluorescence approaches shed light on intracellular RNAs.

Authors:  Sethuramasundaram Pitchiaya; Laurie A Heinicke; Thomas C Custer; Nils G Walter
Journal:  Chem Rev       Date:  2014-01-08       Impact factor: 60.622

5.  Variability of Gene Expression Identifies Transcriptional Regulators of Early Human Embryonic Development.

Authors:  Yu Hasegawa; Deanne Taylor; Dmitry A Ovchinnikov; Ernst J Wolvetang; Laurence de Torrenté; Jessica C Mar
Journal:  PLoS Genet       Date:  2015-08-19       Impact factor: 5.917

6.  Effect of Intrinsic Noise on the Phenotype of Cell Populations Featuring Solution Multiplicity: An Artificial lac Operon Network Paradigm.

Authors:  Ioannis G Aviziotis; Michail E Kavousanakis; Andreas G Boudouvis
Journal:  PLoS One       Date:  2015-07-17       Impact factor: 3.240

Review 7.  Single-molecule fluorescence in situ hybridization: quantitative imaging of single RNA molecules.

Authors:  Sunjong Kwon
Journal:  BMB Rep       Date:  2013-02       Impact factor: 4.778

8.  The importance of tissue specificity for RNA-seq: highlighting the errors of composite structure extractions.

Authors:  Brian R Johnson; Joel Atallah; David C Plachetzki
Journal:  BMC Genomics       Date:  2013-08-28       Impact factor: 3.969

9.  A fully unsupervised compartment-on-demand platform for precise nanoliter assays of time-dependent steady-state enzyme kinetics and inhibition.

Authors:  Fabrice Gielen; Liisa van Vliet; Bartosz T Koprowski; Sean R A Devenish; Martin Fischlechner; Joshua B Edel; Xize Niu; Andrew J deMello; Florian Hollfelder
Journal:  Anal Chem       Date:  2013-04-24       Impact factor: 6.986

10.  Transcriptional mechanisms of cell fate decisions revealed by single cell expression profiling.

Authors:  Victoria Moignard; Berthold Göttgens
Journal:  Bioessays       Date:  2014-01-28       Impact factor: 4.345

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