ArticleNucleic acids research2022
Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes.
Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed, 57 citations in OpenAlex.
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- Insights into novel diagnostic assay development, antimicrobial resistance, and pathogenicity inApplied and environmental microbiology · 2026Article
- Advances in deep learning for antimicrobial research.Frontiers in microbiology · 2026Review
- Antimicrobial Resistance in Bacterial Strains of Agricultural Interest: Predictions Based on Genomic Data.Antibiotics (Basel, Switzerland) · 2025Article
- Challenges and considerations for whole-genome-based antimicrobial resistance plasmid investigations.Antimicrobial agents and chemotherapy · 2025Review
- Rapid Radiations Outweigh Reticulations During the Evolution of a 750-Million-Year-Old Lineage of Cyanobacteria.Molecular biology and evolution · 2025Article
- Analysis of the microbiota of raw commercial feline diets to prioritize food safety investigations.Communications biology · 2025Article
- Plasmids, prophages, and defense systems are depleted from plant microbiota genomes.Genome biology · 2025Article
- Plasmids encode and can mobilize onion pathogenicity in Pantoea agglomerans.The ISME journal · 2025Article
- High-throughput single-cell sequencing of activated sludge microbiome.Environmental science and ecotechnology · 2025Article
- A pan-genome perspective on the evolutionary dynamics of polyphyly, virulence, and antibiotic resistance inCurrent research in food science · 2025Article
- Urban wastewater overflows as hotspots for dissemination of bacteria producing extended-spectrum β-lactamases and carbapenemases in the Suquía River, Argentina.Frontiers in microbiology · 2025Article
- 4CAC: 4-class classifier of metagenome contigs using machine learning and assembly graphs.Nucleic acids research · 2024Article
- Review
- The Putative Virulence Plasmid pYR4 of the Fish PathogenBiology · 2024Article
- Evolutionary genomic analyses of canineApplied and environmental microbiology · 2024Article
- Article
- PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC-ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.
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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.