Journal ArticleDOI
Stochasticity in gene expression: from theories to phenotypes
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TLDR
Stochasticity in gene expression can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.Abstract:
Genetically identical cells exposed to the same environmental conditions can show significant variation in molecular content and marked differences in phenotypic characteristics. This variability is linked to stochasticity in gene expression, which is generally viewed as having detrimental effects on cellular function with potential implications for disease. However, stochasticity in gene expression can also be advantageous. It can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.read more
Citations
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Stochastic Processes in Physics and Chemistry
TL;DR: Van Kampen as mentioned in this paper provides an extensive graduate-level introduction which is clear, cautious, interesting and readable, and could be expected to become an essential part of the library of every physical scientist concerned with problems involving fluctuations and stochastic processes.
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Network motifs: theory and experimental approaches
TL;DR: Network motifs are reviewed, suggesting that they serve as basic building blocks of transcription networks, including signalling and neuronal networks, in diverse organisms from bacteria to humans.
Journal ArticleDOI
Persister cells, dormancy and infectious disease
TL;DR: The molecular mechanisms that underlie the formation of dormant persister cells are now being unravelled and are the focus of this Review.
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Real-Time Kinetics of Gene Activity in Individual Bacteria
TL;DR: This work directly demonstrates transcriptional bursting in Escherichia coli, similar to that indirectly inferred for eukaryotes, and extends protein-based approaches by counting the integer-valued number of transcript with single-molecule resolution.
Journal ArticleDOI
Transcriptome-wide noise controls lineage choice in mammalian progenitor cells
Hannah H. Chang,Martin Hemberg,Martin Hemberg,Mauricio Barahona,Donald E. Ingber,Sui Huang,Sui Huang +6 more
TL;DR: Clonal heterogeneity of gene expression level is not due to independent noise in the expression of individual genes, but reflects metastable states of a slowly fluctuating transcriptome that is distinct in individual cells and may govern the reversible, stochastic priming of multipotent progenitor cells in cell fate decision.
References
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Book
Stochastic processes in physics and chemistry
TL;DR: In this article, the authors introduce the Fokker-planck equation, the Langevin approach, and the diffusion type of the master equation, as well as the statistics of jump events.
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Network biology: understanding the cell's functional organization
TL;DR: This work states that rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize the view of biology and disease pathologies in the twenty-first century.
Stochastic Processes in Physics and Chemistry
Abstract: Preface to the first edition. Preface to the second edition. Abbreviated references. I. Stochastic variables. II. Random events. III. Stochastic processes. IV. Markov processes. V. The master equation. VI. One-step processes. VII. Chemical reactions. VIII. The Fokker-Planck equation. IX. The Langevin approach. X. The expansion of the master equation. XI. The diffusion type. XII. First-passage problems. XIII. Unstable systems. XIV. Fluctuations in continuous systems. XV. The statistics of jump events. XVI. Stochastic differential equations. XVII. Stochastic behavior of quantum systems.
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Stochastic Gene Expression in a Single Cell
TL;DR: This work constructed strains of Escherichia coli that enable detection of noise and discrimination between the two mechanisms by which it is generated and reveals how low intracellular copy numbers of molecules can fundamentally limit the precision of gene regulation.
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A synthetic oscillatory network of transcriptional regulators
TL;DR: This work used three transcriptional repressor systems that are not part of any natural biological clock to build an oscillating network, termed the repressilator, in Escherichia coli, which periodically induces the synthesis of green fluorescent protein as a readout of its state in individual cells.