ArticleiScience2026
SC-MO-GRN-DB: A comprehensive repository for single-cell multiomic gene regulatory networks.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
Funding
Abstract
Gene regulatory networks (GRNs) are essential models for understanding gene expression, cell differentiation, and cellular function. Existing GRN resources primarily focus on transcriptomic data and often overlook the epigenetic mechanisms of gene regulation, limiting evaluation and improvement of GRN inference methods. To address this challenge, we developed SC-MO-GRN-DB, a publicly accessible database of experimentally validated GRNs alongside tissue-matched single-cell multiomic datasets across human and mouse tissues. This repository includes ground-truth GRNs comprising over 22 million regulatory edges, curated from high-confidence experimental datasets. In addition, it hosts multiomic single-cell datasets totaling more than two million cells across six molecular modalities: single-cell RNA sequencing (scRNA-seq), chromatin accessibility (scATAC-seq), chromatin immunoprecipitation (scChIP-seq), DNA methylation (scDNA-Met), chromatin conformation (scHi-C), and gene perturbation screens (scCRISPR-seq). By offering standardized input datasets paired with experimentally supported ground-truth networks, SC-MO-GRN-DB provides a platform for the development, benchmarking, and validation of GRNs with single-cell multiomic data.
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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.