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Zero-shot ecological annotation of microbial genomes with myLLannotator accelerates scientific discovery

Lee, A. L.; Sharma, A.; Maddamsetti, R.

2026-01-21 bioinformatics
10.64898/2026.01.18.700140 bioRxiv
Show abstract

Large language models (LLMs) are promising scientific assistants, but many models remain inaccessible for resource-constrained scientists. To address this, we present myLLannotator, a python package for metadata annotation built on llama3.2-3B. myLLannotator labels 18,000+ genomes in ~2 hours on a laptop, reproducing a discovery involving substantial manual annotation. We use myLLannotator to discover that duplicated genes are depleted in endosymbiotic bacteria, demonstrating its power to accelerate hypothesis testing and discovery.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.