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Related Experiment Video

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Blastomere Explants to Test for Cell Fate Commitment During Embryonic Development
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Computational Analysis of Altering Cell Fate.

Hussein M Abdallah1, Domitilla Del Vecchio2

  • 1Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. hmabdall@mit.edu.

Methods in Molecular Biology (Clifton, N.J.)
|May 8, 2019
PubMed
Summary

Cell fate reprogramming challenges traditional biology views. This study introduces a computational framework using mathematical modeling of gene regulatory networks (GRNs) to analyze cell fate changes.

Keywords:
Cell fateDynamical systemsGene regulatory networkTransdifferentiationiPSC

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Area of Science:

  • Developmental Biology
  • Systems Biology
  • Computational Biology

Background:

  • Cell fate reprogramming challenges the traditional view of fixed cell identity post-differentiation.
  • Advances in somatic cell nuclear transfer, transdifferentiation, and induced pluripotent stem cell (iPSC) reprogramming demonstrate cell fate plasticity.
  • Understanding the genetic and molecular mechanisms underlying cell fate changes is crucial for applications in disease modeling and therapeutics.

Purpose of the Study:

  • To present a computational framework for analyzing cell fate changes.
  • To provide a user guide and tutorials for applying dynamical systems theory to gene regulatory networks (GRNs).
  • To enable the study of intrinsic GRN properties and responses to perturbations during cell fate reprogramming.

Main Methods:

  • Mathematical modeling of gene regulatory networks (GRNs).
  • Application of dynamical systems theory techniques.
  • Computational analysis of GRN properties and dynamic responses.

Main Results:

  • A framework for computationally analyzing cell fate changes is presented.
  • Techniques from dynamical systems theory are provided for probing GRNs.
  • The methods allow for the study of GRN responses to external perturbations.

Conclusions:

  • Gene regulatory networks (GRNs) play a role in cell fate switching.
  • Mathematical modeling of GRNs offers a powerful approach to understand cell fate reprogramming.
  • This framework facilitates research in disease modeling, drug discovery, and clinical therapeutics.