Unraveling the copper-death connection: Decoding COVID-19‘s immune landscape through advanced bioinformatics and machine learning approaches

Unraveling the copper-death connection: Decoding COVID-19‘s immune landscape through advanced bioinformatics and machine learning approaches

ABSTRACTThis study aims to analyze Coronavirus Disease 2019 (COVID-19)-associated copper-death genes using the Gene Expression Omnibus (GEO) dataset and machine learning, exploring their immune microenvironment correlation and underlying mechanisms. Utilizing GEO, we analyzed the GSE217948 dataset w...

Bibliografske podrobnosti
Main Authors:	Qi Wang, Zhenzhong Su, Jing Zhang, He Yan, Jie Zhang
Format:	Article
Jezik:	English
Izdano:	Taylor & Francis Group 2024-12-01
Serija:	Human Vaccines & Immunotherapeutics
Teme:	COVID-19 differential expression genes bioinformatics immune infiltration WGCNA machine learning models
Online dostop:	https://www.tandfonline.com/doi/10.1080/21645515.2024.2310359

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