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

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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Bibliographic Details
Main Authors: Bishesh Subba, Mohammed Toufiq, Fuadur Omi, Marina Yurieva, Taushif Khan, Darawan Rinchai, Karolina Palucka, Damien Chaussabel
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Large language models
Generative artificial intelligence
Biomarkers
Blood transcriptomics
Gene prioritization
Glutathione peroxidase 4
Online Access:https://doi.org/10.1038/s41598-024-73916-5
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https://doi.org/10.1038/s41598-024-73916-5

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