Probabilistic Modeling of Reprogramming to Induced Pluripotent Stem Cells
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Author / Producer
Date
2016-12-20
Publication Type
Journal Article
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no
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Abstract
Reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) is typically an inefficient and asynchronous process. A variety of technological efforts have been made to accelerate and/or synchronize this process. To define a unified framework to study and compare the dynamics of reprogramming under different conditions, we developed an in silico analysis platform based on mathematical modeling. Our approach takes into account the variability in experimental results stemming from probabilistic growth and death of cells and potentially heterogeneous reprogramming rates. We suggest that reprogramming driven by the Yamanaka factors alone is a more heterogeneous process, possibly due to cell-specific reprogramming rates, which could be homogenized by the addition of additional factors. We validated our approach using publicly available reprogramming datasets, including data on early reprogramming dynamics as well as cell count data, and thus we demonstrated the general utility and predictive power of our methodology for investigating reprogramming and other cell fate change systems.
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Publication status
published
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Editor
Book title
Probabilistic Modeling of Reprogramming to Induced Pluripotent Stem Cells
Journal / series
Volume
17 (12)
Pages / Article No.
3395 - 3406
Publisher
Elsevier
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
induced pluripotent stem cells; reprogramming; mathematical/probabilistic modeling; birth-death transition processes
Organisational unit
09626 - Bar-Nur, Ori / Bar-Nur, Ori