ArticleGenome biology2025
DeepCOI: a large language model-driven framework for fast and accurate taxonomic assignment in animal metabarcoding.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Metabarcoding remains challenging due to incomplete taxonomic annotations and computationally intensive processes. We present DeepCOI, a large language model-based classifier pre-trained on seven million cytochrome c oxidase I gene sequences. DeepCOI enables fast and accurate taxonomic assignment across eight major phyla, achieving an AU-ROC of 0.958 and AU-PR of 0.897-outperforming existing methods while significantly reducing inference time. Additionally, DeepCOI demonstrates interpretability by identifying taxonomically informative sequence positions. By integrating large-scale datasets and self-supervised learning, DeepCOI enhances both the accuracy and efficiency of metabarcoding processes, providing a scalable solution for biodiversity assessment and environmental monitoring.
Indexed as
Identifiers
What OpenQuestion holds
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.