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  Stem Cell Differentiation as a Non-Markov Stochastic Process

Stumpf, P. S., Smith, R. C. G., Lenz, M., Schuppert, A., Müller, F.-J., Babtie, A., et al. (2017). Stem Cell Differentiation as a Non-Markov Stochastic Process. Cell Systems, 5(3): e7, pp. 268-282. doi:10.1016/j.cels.2017.08.009.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-85CD-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-85CE-F
Genre: Journal Article

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 Creators:
Stumpf, Patrick S. , Author
Smith, Rosanna C. G. , Author
Lenz, Michael , Author
Schuppert, Andreas , Author
Müller, Franz-Josef1, Author              
Babtie, Ann , Author
Chan, Thalia E. , Author
Stumpf, Michael P. H. , Author
Please, Colin P. , Author
Howison, Sam D. , Author
Arai, Fumio , Author
MacArthur, Ben D. , Author
Affiliations:
1Cellular Phenotyping (Franz-Josef Müller), Dept. of Genome Regulation, (Head: Alexander Meissner), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_3014190              

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Free keywords: lineage commitment; non-Markov process; single-cell biology; statistical mechanics; stem cells; stochastic process
 Abstract: Pluripotent stem cells can self-renew in culture and differentiate along all somatic lineages in vivo. While much is known about the molecular basis of pluripotency, the mechanisms of differentiation remain unclear. Here, we profile individual mouse embryonic stem cells as they progress along the neuronal lineage. We observe that cells pass from the pluripotent state to the neuronal state via an intermediate epiblast-like state. However, analysis of the rate at which cells enter and exit these observed cell states using a hidden Markov model indicates the presence of a chain of unobserved molecular states that each cell transits through stochastically in sequence. This chain of hidden states allows individual cells to record their position on the differentiation trajectory, thereby encoding a simple form of cellular memory. We suggest a statistical mechanics interpretation of these results that distinguishes between functionally distinct cellular "macrostates" and functionally similar molecular "microstates" and propose a model of stem cell differentiation as a non-Markov stochastic process.

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Language(s): eng - English
 Dates: 2017-09-27
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1016/j.cels.2017.08.009
 Degree: -

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Title: Cell Systems
Source Genre: Journal
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Publ. Info: Maryland Heights, MO : Elsevier
Pages: 15 Volume / Issue: 5 (3) Sequence Number: e7 Start / End Page: 268 - 282 Identifier: ISSN: 2405-4720
CoNE: https://pure.mpg.de/cone/journals/resource/2405-4720