ArticleCell systems2020
MATCHA: Probing multi-way chromatin interaction with hypergraph representation learning.
Article in Cell systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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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Who cites it
18 citing papers in PubMed.
- Mega-enhancers compartmentalize transcriptionally active long genes in the brain.Nature cell biology · 2026Article
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.Nature communications · 2026Article
- MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.bioRxiv : the preprint server for biology · 2026Article
- HyperDeepTAD: a topologically associated domains detection method based on multiway chromatin interaction data and deep learning.BMC genomics · 2026Article
- Article
- Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Statistical modeling and significance estimation of multi-way chromatin contacts with HyperloopFinder.Briefings in bioinformatics · 2024Article
- Article
- Computational methods for analysing multiscale 3D genome organization.Nature reviews. Genetics · 2024Review
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- A Lightweight Framework For Chromatin Loop Detection at the Single-Cell Level.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Article
- Prediction of gene co-expression from chromatin contacts with graph attention network.Bioinformatics (Oxford, England) · 2022Article
- Deciphering multi-way interactions in the human genome.Nature communications · 2022Article
- Learning representations of chromatin contacts using a recurrent neural network identifies genomic drivers of conformation.Nature communications · 2022Article
- 3D chromatin architecture and transcription regulation in cancer.Journal of hematology & oncology · 2022Review
- Chromatin Hubs: A biological and computational outlook.Computational and structural biotechnology journal · 2022Review
- Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Recent advances in ligation-free, genome-wide chromatin interaction mapping such as SPRITE and ChIA-Drop have enabled the identification of simultaneous interactions involving multiple genomic loci within the same nuclei, which are informative to delineate higher-order genome organization and gene regulation mechanisms at single-nucleus resolution. Unfortunately, computational methods for analyzing multi-way chromatin interaction data are significantly underexplored. Here we develop an algorithm, called MATCHA, based on hypergraph representation learning where multi-way chromatin interactions are represented as hyperedges. Applications to SPRITE and ChIA-Drop data suggest that MATCHA is effective to denoise the data and make
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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.