ArticleNucleic acids research2025
MetaHiCNet: a web server for normalizing and visualizing microbial Hi-C interaction networks.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Metagenomic Hi‑C Protocols for Viral Genome Binning, Taxonomic Annotation, and Interaction Network Visualization.Current protocols · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Metagenomic Hi-C (metaHi-C) enables the reconstruction of microbial genome organization and interspecies interactions by capturing physical contacts between genomic fragments. However, raw metaHi-C data are often confounded by systematic biases and spurious contacts, which can obscure meaningful biological signals. Existing metaHi-C pipelines typically lack user-friendly normalization workflows and intuitive visualization tools, limiting the ability to explore microbial interaction networks. Here, we introduce MetaHiCNet, a web-based platform that supports widely used normalization methods with customizable parameters. MetaHiCNet provides a stepwise workflow for bias correction, spurious contact removal, and interactive visualization of microbial interactions. The platform supports multiple visualization modes, including taxonomic treemaps, cross-taxa networks, and cross-bin networks, enabling seamless transitions from community-wide overviews to detailed analyses of specific taxa or bins. This functionality facilitates the investigation of host-microbe interactions and the relationships between mobile genetic elements and their microbial hosts, offering deeper insights into microbial community structures and dynamics. MetaHiCNet is freely accessible at www.metahicnet.com without login.
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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.