ArticleBioinformatics advances2023
scMEGA: single-cell multi-omic enhancer-based gene regulatory network inference.
Article in Bioinformatics advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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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.
The trial behind it
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Who cites it
26 citing papers in PubMed, 32 citations in OpenAlex.
- A cross-species single-cell kidney epigenome atlas reveals epithelial-dominant aging-like states in disease.Nature aging · 2026Article
- CpG hypermethylation and WNT/AP-1 cooperativity define the epigenetic landscape and a clinical subgroup of high-risk pediatric adrenocortical carcinoma.Nature communications · 2026Article
- Integrated Single-Nucleus Multi-Omics Atlases Reveal Lineage Plasticity and Regulatory Networks of Luminal Epithelial Cells During Mammary Gland Lactation and Involution.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Epigenetic signatures mark early peripheral human B lineage bifurcation and differential transcriptional profiles in mature populations.Nature communications · 2026Article
- A MEF2C transcription factor network regulates proliferation of glomerular endothelial cells in diabetic kidney disease.Kidney international · 2026Article
- Transient cell states encode positional information to direct asymmetric growth.bioRxiv : the preprint server for biology · 2026Article
- Enhancer-based gene therapy: a new path for precision medicine.Hereditas · 2026Review
- FGFR signaling establishes spatial gradients of secretory cell identities along the airway proximal-distal axis.Nature communications · 2026Article
- Single-cell atlas of the developing Down syndrome brain cortex.Nature medicine · 2026Article
- PHLOWER leverages single-cell multimodal data to infer complex, multi-branching cell differentiation trajectories.Nature methods · 2025Article
- Sex differences in the developing human cortex intersect with genetic risk of neurodevelopmental disorders.bioRxiv : the preprint server for biology · 2025Article
- Leveraging transcription factor physical proximity for enhancing gene regulation inference.Bioinformatics (Oxford, England) · 2025Article
- Advances and challenges in cell-cell communication inference: a comprehensive review of tools, resources, and future directions.Briefings in bioinformatics · 2025Review
- scMultiMap: Cell-type-specific mapping of enhancers and target genes from single-cell multimodal data.Nature communications · 2025Article
- A large-scale benchmark for network inference from single-cell perturbation data.Communications biology · 2025Article
- Inferring gene regulatory networks from time-series scRNA-seq data via GRANGER causal recurrent autoencoders.Briefings in bioinformatics · 2025Article
- Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data.Molecular systems biology · 2025Review
- A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data.Briefings in bioinformatics · 2024Review
- Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data.Briefings in bioinformatics · 2024Article
- Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights.BioEssays : news and reviews in molecular, cellular and developmental biology · 2024Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Summary: The increasing availability of single-cell multi-omics data allows to quantitatively characterize gene regulation. We here describe scMEGA (Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference) that enables an end-to-end analysis of multi-omics data for gene regulatory network inference including modalities integration, trajectory analysis, enhancer-to-promoter association, network analysis and visualization. This enables to study the complex gene regulation mechanisms for dynamic biological processes, such as cellular differentiation and disease-driven cellular remodeling. We provide a case study on gene regulatory networks controlling myofibroblast activation in human myocardial infarction. Availability and implementation: scMEGA is implemented in R, released under the MIT license and available from https://github.com/CostaLab/scMEGA. Tutorials are available from https://costalab.github.io/scMEGA. Supplementary information: Supplementary data are available at
Identifiers
What OpenQuestion holds
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.