The timing of cellular events: a stochastic vs deterministic perspective Article Swipe
Lucy Ham
,
Megan A. Coomer
,
Kaan Öcal
,
Ramon Grima
,
Michael P. H. Stumpf
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.07.20.549956
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.07.20.549956
Changes in cell state are driven by key molecular events whose timing can often be measured experimentally. Of particular interest is the time taken for the levels of RNA or protein molecules to reach a critical threshold defining the triggering of a cellular event. While this mean trigger time can be estimated by numerical integration of deterministic models, these ignore intrinsic noise and hence their predictions may be inaccurate. Here we study the differences between deterministic and stochastic model predictions for the mean trigger times using simple models of gene expression, post-transcriptional feedback control, and enzyme-mediated catalysis. By comparison of the two predictions, we show that when promoter switching is present there exists a transition from a parameter regime where deterministic models predict a longer trigger time than stochastic models to a regime where the opposite occurs. Furthermore, the ratio of the trigger times of the two models can be large, particularly for auto-regulatory genetic feedback loops. Our theory provides intuitive insight into the origin of these effects and shows that deterministic predictions for cellular event timing can be highly inaccurate when molecule numbers are within the range known for many cells.
Related Topics
Concepts
Statistical physics
Event (particle physics)
Stochastic modelling
Noise (video)
Computer science
Perspective (graphical)
Range (aeronautics)
Stochastic process
Biological system
Physics
Mathematics
Biology
Statistics
Artificial intelligence
Quantum mechanics
Materials science
Image (mathematics)
Composite material
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.07.20.549956
- https://www.biorxiv.org/content/biorxiv/early/2023/07/21/2023.07.20.549956.full.pdf
- OA Status
- green
- Cited By
- 2
- References
- 68
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385074905
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4385074905Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.07.20.549956Digital Object Identifier
- Title
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The timing of cellular events: a stochastic vs deterministic perspectiveWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-07-21Full publication date if available
- Authors
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Lucy Ham, Megan A. Coomer, Kaan Öcal, Ramon Grima, Michael P. H. StumpfList of authors in order
- Landing page
-
https://doi.org/10.1101/2023.07.20.549956Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2023/07/21/2023.07.20.549956.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2023/07/21/2023.07.20.549956.full.pdfDirect OA link when available
- Concepts
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Statistical physics, Event (particle physics), Stochastic modelling, Noise (video), Computer science, Perspective (graphical), Range (aeronautics), Stochastic process, Biological system, Physics, Mathematics, Biology, Statistics, Artificial intelligence, Quantum mechanics, Materials science, Image (mathematics), Composite materialTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2Per-year citation counts (last 5 years)
- References (count)
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68Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_year | 2023 |
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