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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Bishesh Subba, Mohammed Toufiq, Fuadur Omi, Marina Yurieva, Taushif Khan, Darawan Rinchai, Karolina Palucka, Damien Chaussabel
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Nature Portfolio 2024-10-01
Sarja:	Scientific Reports
Aiheet:	Large language models Generative artificial intelligence Biomarkers Blood transcriptomics Gene prioritization Glutathione peroxidase 4
Linkit:	https://doi.org/10.1038/s41598-024-73916-5
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