Gene regulatory network inference in the era of single-cell multi-omics

Summary

This narrative review examines computational methods for inferring gene regulatory networks from single-cell multi-omics data, a rapidly evolving field in molecular systems biology. The authors survey recent approaches that integrate multiple molecular layers—transcriptomics, proteomics, chromatin accessibility—to reconstruct cell-type-specific regulatory relationships. As suggested by the publication date and journal scope, the review likely consolidates emerging best practices and identifies methodological gaps in network inference at single-cell resolution.

Regional applicability

This is a methods paper in molecular systems biology with limited direct application to UK farming systems or agricultural practice. Its relevance to Vitagri's scope is tangential unless applied to plant systems biology or crop trait regulation research.

Key measures

Computational methods for gene regulatory network inference; integration of transcriptomics, proteomics, and chromatin accessibility data; network inference accuracy and robustness metrics; methodological comparisons

Outcomes reported

The paper reviews computational and methodological approaches for inferring gene regulatory networks from single-cell multi-omics datasets, which integrate multiple molecular measurement types at cellular resolution. It synthesises state-of-the-art techniques and discusses their applications and limitations.

Topic tags