Human-augmented large language model-driven selection of glutathione peroxidase 4 as a candidate blood transcriptional biomarker for circulating erythroid cells

Abstract The identification of optimal candidate genes from large-scale blood transcriptomic data is crucial for developing targeted assays to monitor immune responses. Here, we introduce a novel, optimized large language model (LLM)-based approach for prioritizing candidate biomarkers from blood tr...

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Автори:	Bishesh Subba, Mohammed Toufiq, Fuadur Omi, Marina Yurieva, Taushif Khan, Darawan Rinchai, Karolina Palucka, Damien Chaussabel
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Nature Portfolio 2024-10-01
Серія:	Scientific Reports
Предмети:	Large language models Generative artificial intelligence Biomarkers Blood transcriptomics Gene prioritization Glutathione peroxidase 4
Онлайн доступ:	https://doi.org/10.1038/s41598-024-73916-5
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