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A multi-step completion process model of cell plasticity.

Chen M Chen1, Rosemary Yu1

  • 1Department of Molecular Developmental Biology, Radboud Institute for Molecular Life Sciences, Faculty of Science, Radboud University, Geert Grooteplein-Zuid 26-28, Nijmegen, 6525GA, The Netherlands.

Briefings in Bioinformatics
|April 14, 2025
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Summary
This summary is machine-generated.

This study introduces a novel mathematical framework to model cell plasticity as a multi-step process. The model accurately predicts molecular changes during cell plasticity and offers insights for biomedical interventions.

Keywords:
cell plasticitycompletion processmathematical modelingtime-series omics data

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Area of Science:

  • Cellular biology
  • Systems biology
  • Mathematical modeling

Background:

  • Cell plasticity is crucial for biological processes but lacks predictive mathematical models.
  • Understanding molecular behaviors in cell plasticity is essential for biological research.

Purpose of the Study:

  • To develop a novel mathematical framework for modeling cell plasticity.
  • To predict molecular behaviors and outcomes during cell plasticity programs.

Main Methods:

  • Modeled cell plasticity as a multi-step completion process with intermediate attractors.
  • Utilized omics time-series data as input for the mathematical framework.
  • Validated predictions against experimental data and domain knowledge.

Main Results:

  • The framework accurately fits omics time-series data.
  • Identified key attractor states, their timing, and molecular markers.
  • Achieved quantitative, time-resolved predictions of plasticity program outcomes (R2 of 0.53-0.63).

Conclusions:

  • The developed mathematical model provides a robust tool for studying cell plasticity.
  • The model offers quantitative insights and predictive capabilities for patient-derived data.
  • This framework can guide future research and potential biomedical interventions for cell plasticity-related processes.