ArticleNucleic acids research2024
scGRN: a comprehensive single-cell gene regulatory network platform of human and mouse.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- SC-MO-GRN-DB: A comprehensive repository for single-cell multiomic gene regulatory networks.iScience · 2026Article
- Deep learning-based semantic matching of cis-regulatory DNA sequences facilitates the prediction of gene function.Nature plants · 2026Article
- Drug Discovery from Gene Expression/Gene Regulation.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Single-cell transcriptomics reveals an abnormal immune microenvironment in plasma cell mastitis.Annals of medicine · 2025Article
- Microarray and Single-Cell RNA Sequencing Reveals G-Protein Gene Expression Signatures of Spermatogonia Stem Cell.Stem cell reviews and reports · 2025Article
- scPlantLLM: A Foundation Model for Exploring Single-cell Expression Atlases in Plants.Genomics, proteomics & bioinformatics · 2025Article
- scMINER: a mutual information-based framework for clustering and hidden driver inference from single-cell transcriptomics data.Nature communications · 2025Article
- Single-cell transcriptomics reveals liver developmental trajectory during lineage reprogramming of human induced hepatocyte-like cells.Cellular and molecular life sciences : CMLS · 2025Article
- AnomalGRN: deciphering single-cell gene regulation network with graph anomaly detection.BMC biology · 2025Article
- Intratumoral Heterogeneity and Immune Microenvironment in Hepatoblastoma Revealed by Single-Cell RNA Sequencing.Journal of cellular and molecular medicine · 2025Article
- A Current Perspective of Medical Informatics Developments for a Clinical Translation of (Non-coding)RNAs and Single-Cell Technologies.Methods in molecular biology (Clifton, N.J.) · 2025Article
- DiabetesOmic: A comprehensive multi-omics diabetes database.Computational and structural biotechnology journal · 2025Article
- Knowledge-based inductive bias and domain adaptation for cell type annotation.Communications biology · 2024Article
- Artificial intelligence and machine learning applications for cultured meat.Frontiers in artificial intelligence · 2024Review
- Integration of Single-Cell RNA and Bulk RNA Sequencing Reveals Cellular Heterogeneity and Identifies Survival-Associated Regulatory Networks in Glioblastoma.IET systems biologyArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Gene regulatory networks (GRNs) are interpretable graph models encompassing the regulatory interactions between transcription factors (TFs) and their downstream target genes. Making sense of the topology and dynamics of GRNs is fundamental to interpreting the mechanisms of disease etiology and translating corresponding findings into novel therapies. Recent advances in single-cell multi-omics techniques have prompted the computational inference of GRNs from single-cell transcriptomic and epigenomic data at an unprecedented resolution. Here, we present scGRN (https://bio.liclab.net/scGRN/), a comprehensive single-cell multi-omics gene regulatory network platform of human and mouse. The current version of scGRN catalogs 237 051 cell type-specific GRNs (62 999 692 TF-target gene pairs), covering 160 tissues/cell lines and 1324 single-cell samples. scGRN is the first resource documenting large-scale cell type-specific GRN information of diverse human and mouse conditions inferred from single-cell multi-omics data. We have implemented multiple online tools for effective GRN analysis, including differential TF-target network analysis, TF enrichment analysis, and pathway downstream analysis. We also provided details about TF binding to promoters, super-enhancers and typical enhancers of target genes in GRNs. Taken together, scGRN is an integrative and useful platform for searching, browsing, analyzing, visualizing and downloading GRNs of interest, enabling insight into the differences in regulatory mechanisms across diverse conditions.
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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 OpenQuestion graph.