Literature DB >> 18958456

Determining biological noise via single cell analysis.

Edgar A Arriaga1.   

Abstract

Single cell analysis techniques describe the cellular heterogeneity that originates from fundamental stochastic variations in each of the molecular processes underlying cell function. The quantitative description of this set of variations is called biological noise and includes intrinsic and extrinsic noise. The former refers to stochastic variations directly involved with a given process, while the latter is due to environmental factors associated with other processes. Mathematical models are successful in predicting noise trends in simple biological systems, but it takes single cell techniques such as flow cytometry and time lapse microscopy to determine and dissect biological noise. This review describes several approaches that have been successfully used to describe biological noise.

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Year:  2008        PMID: 18958456      PMCID: PMC3035192          DOI: 10.1007/s00216-008-2431-z

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


  44 in total

1.  Circadian clocks limited by noise.

Authors:  N Barkai; S Leibler
Journal:  Nature       Date:  2000-01-20       Impact factor: 49.962

2.  Regulation of noise in the expression of a single gene.

Authors:  Ertugrul M Ozbudak; Mukund Thattai; Iren Kurtser; Alan D Grossman; Alexander van Oudenaarden
Journal:  Nat Genet       Date:  2002-04-22       Impact factor: 38.330

3.  Self-organized living systems: conjunction of a stable organization with chaotic fluctuations in biological space-time.

Authors:  Charles Auffray; Sandrine Imbeaud; Magali Roux-Rouquié; Leroy Hood
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2003-06-15       Impact factor: 4.226

4.  Simultaneously monitoring gene expression kinetics and genetic noise in single cells by optical well arrays.

Authors:  Yina Kuang; Israel Biran; David R Walt
Journal:  Anal Chem       Date:  2004-11-01       Impact factor: 6.986

5.  Molecular communication through stochastic synchronization induced by extracellular fluctuations.

Authors:  Tianshou Zhou; Luonan Chen; Kazuyuki Aihara
Journal:  Phys Rev Lett       Date:  2005-10-19       Impact factor: 9.161

6.  Contributions of low molecule number and chromosomal positioning to stochastic gene expression.

Authors:  Attila Becskei; Benjamin B Kaufmann; Alexander van Oudenaarden
Journal:  Nat Genet       Date:  2005-08-07       Impact factor: 38.330

7.  Biological physics: harmonies from noise.

Authors:  Michael Springer; Johan Paulsson
Journal:  Nature       Date:  2006-01-05       Impact factor: 49.962

8.  Posttranscriptional regulation of smoothened is part of a self-correcting mechanism in the Hedgehog signaling system.

Authors:  J Alcedo; Y Zou; M Noll
Journal:  Mol Cell       Date:  2000-08       Impact factor: 17.970

9.  Oscillations and variability in the p53 system.

Authors:  Naama Geva-Zatorsky; Nitzan Rosenfeld; Shalev Itzkovitz; Ron Milo; Alex Sigal; Erez Dekel; Talia Yarnitzky; Yuvalal Liron; Paz Polak; Galit Lahav; Uri Alon
Journal:  Mol Syst Biol       Date:  2006-06-13       Impact factor: 11.429

10.  Accurate prediction of gene feedback circuit behavior from component properties.

Authors:  Nitzan Rosenfeld; Jonathan W Young; Uri Alon; Peter S Swain; Michael B Elowitz
Journal:  Mol Syst Biol       Date:  2007-11-13       Impact factor: 11.429

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  9 in total

Review 1.  The role of physiological heterogeneity in microbial population behavior.

Authors:  Mary E Lidstrom; Michael C Konopka
Journal:  Nat Chem Biol       Date:  2010-09-17       Impact factor: 15.040

Review 2.  Measuring enzyme activity in single cells.

Authors:  Michelle L Kovarik; Nancy L Allbritton
Journal:  Trends Biotechnol       Date:  2011-02-11       Impact factor: 19.536

Review 3.  The impact of non-genetic heterogeneity on cancer cell death.

Authors:  Zintis Inde; Scott J Dixon
Journal:  Crit Rev Biochem Mol Biol       Date:  2017-12-18       Impact factor: 8.250

4.  Photoactivatable Reporter to Perform Multiplexed and Temporally Controlled Measurements of Kinase and Protease Activity in Single Cells.

Authors:  Matthew M Anttila; Brianna M Vickerman; Qunzhao Wang; David S Lawrence; Nancy L Allbritton
Journal:  Anal Chem       Date:  2021-12-04       Impact factor: 6.986

5.  Analysis of single-cell cytokine secretion reveals a role for paracrine signaling in coordinating macrophage responses to TLR4 stimulation.

Authors:  Qiong Xue; Yao Lu; Markus R Eisele; Endah S Sulistijo; Nafeesa Khan; Rong Fan; Kathryn Miller-Jensen
Journal:  Sci Signal       Date:  2015-06-16       Impact factor: 9.517

6.  Symposium on single cell analysis and genomic approaches, Experimental Biology 2017 Chicago, Illinois, April 23, 2017.

Authors:  Hilary A Coller
Journal:  Physiol Genomics       Date:  2017-08-11       Impact factor: 4.297

Review 7.  The function of chromatin modifiers in lineage commitment and cell fate specification.

Authors:  Jason Signolet; Brian Hendrich
Journal:  FEBS J       Date:  2014-11-20       Impact factor: 5.542

8.  Systematic analysis of noise reduction properties of coupled and isolated feed-forward loops.

Authors:  Suchana Chakravarty; Attila Csikász-Nagy
Journal:  PLoS Comput Biol       Date:  2021-12-03       Impact factor: 4.475

9.  Modeling heterogeneous responsiveness of intrinsic apoptosis pathway.

Authors:  Hsu Kiang Ooi; Lan Ma
Journal:  BMC Syst Biol       Date:  2013-07-23
  9 in total

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