ArticleNature communications2022
A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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Who cites it
97 citing papers in PubMed, 173 citations in OpenAlex.
- Gut microbial markers of immunotherapy response in melanoma: a cross-cohort analysis including the first Russian dataset.Gut microbes · 2026Article
- DecBin: Bayesian-optimized deep clustering for long-read metagenomic binning.Briefings in bioinformatics · 2026Article
- Deployable high-fidelity metagenome binning at scale with QuickBin.Communications biology · 2026Article
- Computational Genomics for Resistome Characterization: Current Advancements and Future Challenges Under a One Health Perspective.Antibiotics (Basel, Switzerland) · 2026Review
- Integrated gut microbiota and metabolome signatures revealed by deep metagenomic sequencing in post-stroke cognitive impairment with type 2 diabetes.Microbiology spectrum · 2026Article
- VirBinn improves viral genome binning from metagenomic Hi-C through graph diffusion.Bioinformatics (Oxford, England) · 2026Article
- Mobile genetic elements shape microbial diversity and functions in thawing permafrost soils.Nature microbiology · 2026Article
- Increased abundance of Limosilactobacillus reuteri in the gut of selectively bred high-tameness mice and its association with behavioural changes.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026Article
- META-DIFF: a k-mer-based pipeline that detects differentially abundant sequences in metagenomics whole genome sequencing.Scientific reports · 2026Article
- AI-empowered human microbiome research.Gut · 2026Review
- Viral Assemblages of a Hypersaline Estuary Show Divergent Responses to Freshwater and Temperature Disturbances.Environmental microbiology reports · 2026Article
- Dual human milk oligosaccharide-fibre utilisation is a selection cue for the weaning gut microbiome.Nature communications · 2026Observational
- Two-hourly resolved microbial and viral dynamics in the subtropical Daya Bay.Scientific data · 2026Article
- Advances and future directions in identifying specific taxa from microbial meta-omics data: from pipeline to deep learning.mSystems · 2026Review
- A bifidobacterial enzyme orchestrates ecology and function of infant gut bacterial community.bioRxiv : the preprint server for biology · 2026Article
- Improving metagenome binning by integrating intrinsic features and taxonomy.Nature biotechnology · 2026Article
- Comprehensive benchmarking of metagenomic binning tools reveals key factors for improved genome recovery.Nature communications · 2026Article
- CAMP: a modular metagenomics analysis system for integrated multistep data exploration.NAR genomics and bioinformatics · 2026Article
- Unique ecology of co-occurring functionally and phylogenetically undescribed species in the infant oral microbiome.PLoS computational biology · 2026Article
- Experimental insights in taxon-specific functional responses to droughts in glacier-fed stream biofilms.Microbiome · 2026Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and enable the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we introduce SemiBin, an open source tool that uses deep siamese neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of reconstructing high-quality bins that are outside the reference dataset. Using simulated and real microbiome datasets from several different habitats from GMGCv1 (Global Microbial Gene Catalog), including the human gut, non-human guts, and environmental habitats (ocean and soil), we show that SemiBin outperforms existing state-of-the-art binning methods. In particular, compared to other methods, SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species.
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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.