Systems biology of stem cell fate and cellular reprogramming
Systems biology of stem cell fate and cellular reprogramming
Stem cell differentiation and the maintenance of self-renewal are intrinsically complex processes requiring the coordinated dynamic expression of hundreds of genes and proteins in precise response to external signalling cues. Numerous recent reports have used both experimental and computational techniques to dissect this complexity. These reports suggest that the control of cell fate has both deterministic and stochastic elements: complex underlying regulatory networks define stable molecular 'attractor' states towards which individual cells are drawn over time, whereas stochastic fluctuations in gene and protein expression levels drive transitions between coexisting attractors, ensuring robustness at the population level.
672-681
MacArthur, Ben D.
2c0476e7-5d3e-4064-81bb-104e8e88bb6b
Ma'ayan, Avi
74c9899b-5532-4865-96d9-11bac1c27f62
Lemischka, Ihor R.
3deafa24-f76b-4bfa-90e3-e2b802786bdc
October 2009
MacArthur, Ben D.
2c0476e7-5d3e-4064-81bb-104e8e88bb6b
Ma'ayan, Avi
74c9899b-5532-4865-96d9-11bac1c27f62
Lemischka, Ihor R.
3deafa24-f76b-4bfa-90e3-e2b802786bdc
MacArthur, Ben D., Ma'ayan, Avi and Lemischka, Ihor R.
(2009)
Systems biology of stem cell fate and cellular reprogramming.
Nature Reviews Molecular Cell Biology, 10 (10), .
(doi:10.1038/nrm2766).
(PMID:19738627)
Abstract
Stem cell differentiation and the maintenance of self-renewal are intrinsically complex processes requiring the coordinated dynamic expression of hundreds of genes and proteins in precise response to external signalling cues. Numerous recent reports have used both experimental and computational techniques to dissect this complexity. These reports suggest that the control of cell fate has both deterministic and stochastic elements: complex underlying regulatory networks define stable molecular 'attractor' states towards which individual cells are drawn over time, whereas stochastic fluctuations in gene and protein expression levels drive transitions between coexisting attractors, ensuring robustness at the population level.
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Published date: October 2009
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Local EPrints ID: 173787
URI: http://eprints.soton.ac.uk/id/eprint/173787
ISSN: 1471-0072
PURE UUID: 2245c9be-c629-403f-857c-fb0476ef1ab5
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Date deposited: 07 Feb 2011 14:23
Last modified: 14 Mar 2024 02:44
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Author:
Avi Ma'ayan
Author:
Ihor R. Lemischka
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