ArticleCommunications biology2023
Adversarial and variational autoencoders improve metagenomic binning.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed.
- DecBin: Bayesian-optimized deep clustering for long-read metagenomic binning.Briefings in bioinformatics · 2026Article
- Two-hourly resolved microbial and viral dynamics in the subtropical Daya Bay.Scientific data · 2026Article
- Improving metagenome binning by integrating intrinsic features and taxonomy.Nature biotechnology · 2026Article
- Deciphering the etiology of the 2024 outbreak of undiagnosed febrile illness in Panzi, Democratic Republic of the Congo.Nature medicine · 2026Article
- Accurate plasmid reconstruction from metagenomics data using assembly-alignment graphs and contrastive learning.Nature biotechnology · 2026Article
- Microbial succession and assembly shaped by sulfur, spatial partitioning, and water flow in a volcanic acidic river of northern Patagonia.The ISME journal · 2026Article
- Reference-free k-mer based dissimilarity measures for metagenomes comparison.Frontiers in bioinformatics · 2026Article
- Genome-resolved metagenomics reveals rare taxa and functional traits in two contrasting agricultural fields.ISME communications · 2026Article
- The Role of Nucleotide Sequencing in Natural Product Drug Discovery.Journal of natural products · 2025Review
- LorBin: efficient binning of long-read metagenomes by multiscale adaptive clustering and evaluation.Nature communications · 2025Article
- Dataset of 111 metagenome-assembled genomes from cattle manure, soil and manured soil samples.Data in brief · 2025Article
- Genome-resolved metagenomics from short-read sequencing data in the era of artificial intelligence.Functional & integrative genomics · 2025Review
- A review of neural networks for metagenomic binning.Briefings in bioinformatics · 2025Review
- Complementary insights into gut viral genomes: a comparative benchmark of short- and long-read metagenomes using diverse assemblers and binners.Microbiome · 2024Article
- Binning Metagenomic Contigs Using Contig Embedding and Decomposed Tetranucleotide Frequency.Biology · 2024Article
- Solving genomic puzzles: computational methods for metagenomic binning.Briefings in bioinformatics · 2024Review
- Genome-resolved metagenomics: a game changer for microbiome medicine.Experimental & molecular medicine · 2024Review
- Deep learning methods in metagenomics: a review.Microbial genomics · 2024Review
- Recovery of 1887 metagenome-assembled genomes from the South China Sea.Scientific data · 2024Article
- Deep learning in microbiome analysis: a comprehensive review of neural network models.Frontiers in microbiology · 2024Review
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Assembly of reads from metagenomic samples is a hard problem, often resulting in highly fragmented genome assemblies. Metagenomic binning allows us to reconstruct genomes by re-grouping the sequences by their organism of origin, thus representing a crucial processing step when exploring the biological diversity of metagenomic samples. Here we present Adversarial Autoencoders for Metagenomics Binning (AAMB), an ensemble deep learning approach that integrates sequence co-abundances and tetranucleotide frequencies into a common denoised space that enables precise clustering of sequences into microbial genomes. When benchmarked, AAMB presented similar or better results compared with the state-of-the-art reference-free binner VAMB, reconstructing ~7% more near-complete (NC) genomes across simulated and real data. In addition, genomes reconstructed using AAMB had higher completeness and greater taxonomic diversity compared with VAMB. Finally, we implemented a pipeline Integrating VAMB and AAMB that enabled improved binning, recovering 20% and 29% more simulated and real NC genomes, respectively, compared to VAMB, with moderate additional runtime.
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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.