{
  "abstract": "Microorganisms exert profound influences on both natural ecosystems and human society. As the cornerstone of microbial research, metagenomics relies on the precise analysis of large-scale, multi-source genomic data. However, discriminating among diverse sequence types remains a formidable challenge. To address this, we present CamFi (Codon-aware Multi-scale Feature Fusion), a unified framework integrating overlapping nucleotide-triplet representations with multi-scale dilated convolutions for classifying prokaryotic chromosomes, eukaryotic chromosomes, plasmids, and viruses. Benchmark evaluations demonstrate strong mean F1 scores of 97.70% for eukaryotic chromosomes and 94.13% for plasmids. On the CAMI II marine dataset, CamFi achieved a weighted F1 of 82.65%, ranking second among six methods based on reported aggregate metrics. In a balanced four-class benchmark, CamFi attained a macro-F1 of 93.77%, compared with DeepMicroClass (90.03%) and the XGBoost stage of 4CAC (64.66%). These results establish CamFi as a competitive approach for unified metagenomic contig classification under the evaluated conditions.",
  "abstract_shown": true,
  "affiliations": [
    "School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, People’s Republic of China",
    "Shanghai Key Laboratory of Power Station Automation Technology, Shanghai, People’s Republic of China"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yan Qian"
    },
    {
      "affs": [
        1
      ],
      "name": "Quanjie Song"
    },
    {
      "name": "Xinyi Xie"
    },
    {
      "name": "Li Deng"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bthcytqvbz7sr.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0359090",
  "fulltext_url": null,
  "id": "bthcytqvbz7sr",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0359090",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Genomics and Phylogenetic Studies"
    ],
    [
      "plos",
      "/Biology and life sciences/Computational biology/Genome analysis/Genomic databases"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics/Genomics"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics/Genomics/Genome analysis/Genomic databases"
    ],
    [
      "plos",
      "/Biology and life sciences/Genetics/Genomics/Metagenomics"
    ],
    [
      "plos",
      "/Biology and life sciences/Organisms/Eukaryota"
    ],
    [
      "plos",
      "/Biology and life sciences/Organisms/Viruses/RNA viruses"
    ],
    [
      "plos",
      "/Biology and life sciences/Taxonomy"
    ],
    [
      "plos",
      "/Computer and information sciences/Data management/Taxonomy"
    ],
    [
      "plos",
      "/Research and analysis methods/Database and informatics methods/Bioinformatics/Sequence analysis/Sequence databases"
    ],
    [
      "plos",
      "/Research and analysis methods/Database and informatics methods/Biological databases/Genomic databases"
    ],
    [
      "plos",
      "/Research and analysis methods/Database and informatics methods/Biological databases/Sequence databases"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Mathematical functions/Convolution"
    ]
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  "openalex": "W7220416847",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0359090&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/bthcytqvbz7sr.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:37Z",
      "native_id": "10.1371/journal.pone.0359090",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0359090"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:computational biology",
      "subfield": "bioinformatics"
    },
    {
      "field": "biology",
      "origin": "plos:genomics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Codon-aware multi-scale feature fusion for metagenomic sequence classification",
  "title_text": "Codon-aware multi-scale feature fusion for metagenomic sequence classification",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:37Z",
  "url": "https://research.draconitic.com/paper/bthcytqvbz7sr",
  "venue": "PLOS One",
  "versions": []
}