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GPTON: Generative Pre-trained Transformers enhanced with Ontology Narration for accurate annotation of biological data

2024-10-12 · Rongbin Li, Wenbo Chen, Jinbo Li, Hanwen Xing, Hua Xu, Zhao Li, W. Jim Zheng

By leveraging GPT-4 for ontology narration, we developed GPTON to infuse structured knowledge into LLMs through verbalized ontology terms, achieving accurate text and ontology annotations for over 68% of gene sets in the top five predictions. Manual evaluations confirm GPTON's robustness, highlighting its potential to harness LLMs and structured knowledge to significantly advance biomedical research beyond gene set annotation.

📄 PDF Abstract BibTeX arXiv:2410.10899

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Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…
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Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

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