Probabilistic Modeling of Reprogramming to Induced Pluripotent Stem Cells Academic Article Article uri icon

Overview

MeSH Major

  • Cell Differentiation
  • Cell Lineage
  • Induced Pluripotent Stem Cells

abstract

  • ¬© 2016 The Authors 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.

publication date

  • December 20, 2016

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1016/j.celrep.2016.11.080

PubMed ID

  • 28009305

Additional Document Info

start page

  • 3395

end page

  • 3406

volume

  • 17

number

  • 12