MetageNN
Feed-forward neural network on 6-mer profiles of 1 kbp sequences sampled from reference genomes; long reads are split into 1 kbp chunks and classified by majority vote at genus level.
Results are recorded on linked configurations and versions of this model. Their settings and evaluations are kept separate below.
Results on linked records
This model has no results of its own in this release. One linked record has results. They are not assigned to the underlying model: each record keeps its own settings and evaluations, and its scores are on its own page.
- MetageNN (main database, Peres da Silva et al. 2024) Configuration · configuration · 3 evaluations · 5 results
Overview
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How it works, versions and access
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Evidence
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Evidence table
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Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
1 source record and release history
- MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes · Original source · BMC Bioinformatics 25:153, published 2024-04-16; PMC11022314 full-text XML
Technical metadata and extraction receipts
Stable ID: dna-pathogen-20261012-metagenn-model-metagenn
- areas
- microbes-communities
- contexts
- research
- method types
- supervised_machine_learning
- reported name
- MetageNN
- entity level
- family
- source locator
- Background paragraph 4; Results 'MetageNN presents a higher F1 score than GeNet...' Experimental setup; Fig. 5 caption
- access
- Code and genome lists at https://github.com/csb5/MetageNN (no licence file; not pinned in this pass)
- training data
- Main database: 516 RefSeq genomes (505 species, 311 genera); training set of about 17 million 1 kbp sequences at 8x coverage
- missing metadata
- version: reason: inapplicable; note: Family record; the evaluated model is the configuration
- review
- method: source-hash-verification; scope-review; reviewer: claude; reviewer note: Separate Claude review agent (rev-mlvb), independent of the extracting agent; no human review claimed; date: 2026-10-12; artifact sha256: ac4b137508d295d5e04e9be263bef40bdcf2c494e096407e5896611194f14e12; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11022314/fullTextXML; note: Checked against the re-downloaded article XML (SHA-256 matches).
Related records
- configuration of: MetageNN (main database, Peres da Silva et al. 2024)