ArticleBioinformatics (Oxford, England)2025
Dynamic gene regulatory network inference from single-cell data using optimal transport.
Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- DataXflowGen for GenAI-driven model generation.Scientific reports · 2026Article
- Multi-omic network inference from time-series data.NPJ systems biology and applications · 2025Article
- Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation.PLoS computational biology · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
motivationModelling gene expression is a central problem in systems biology. Single-cell technologies have revolutionized the field by enabling sequencing at the resolution of individual cells. This results in a much richer data compared to what is obtained by bulk technologies, offering new possibilities and challenges for gene regulatory network inference.
resultsIn this work, we introduce GRIT (gene regulation inference by transport)-a method to fit a differential equation model and to infer gene regulatory networks from single-cell data using the theory of optimal transport. The idea consists in tracking the evolution of the cell distribution over time and finding the system whose temporal marginals minimize the transport cost with the observations. GRIT is finally used to identify genes and pathways affected by two Parkinson's disease associated mutations. AVAILABILITY AND IMPLEMENTATION: Matlab implementation of the method and code for data generation are at gitlab.com/uniluxembourg/lcsb/systems-control/grit together with a user guide. A snapshot of the code used for the results of this article is at doi: 10.5281/zenodo.15582432.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.