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Updated: Sep 16, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Dynamic gene regulatory network inference from single-cell data using optimal transport.

François Lamoline1, Isabel Haasler2,3, Johan Karlsson3

  • 1Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, L-4367, Luxembourg.

Bioinformatics (Oxford, England)
|July 12, 2025
PubMed
Summary
This summary is machine-generated.

We developed GRIT, a new method for inferring gene regulatory networks from single-cell data using optimal transport theory. This approach helps identify genes and pathways impacted by Parkinson's disease mutations.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Genomics

Background:

  • Gene expression modeling is crucial in systems biology.
  • Single-cell technologies provide high-resolution data, presenting new challenges for gene regulatory network inference.
  • Existing methods struggle with the complexity of single-cell data.

Purpose of the Study:

  • To introduce GRIT (gene regulation inference by transport), a novel method for gene regulatory network inference.
  • To apply GRIT to single-cell data to understand gene regulation dynamics.
  • To identify genes and pathways affected by Parkinson's disease mutations.

Main Methods:

  • Utilizing the theory of optimal transport to model gene expression.
  • Fitting a differential equation model to single-cell data.
  • Tracking cell distribution evolution over time to infer regulatory networks.

Main Results:

  • GRIT successfully infers gene regulatory networks from single-cell data.
  • The method identifies key genes and pathways influenced by Parkinson's disease mutations.
  • GRIT leverages optimal transport to analyze temporal changes in cell populations.

Conclusions:

  • GRIT offers a powerful new approach for gene regulatory network inference from single-cell data.
  • The method has direct applications in understanding disease mechanisms, such as Parkinson's disease.
  • Optimal transport theory provides a robust framework for analyzing complex biological systems.