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Identification and validation of potential genes for the diagnosis of sepsis by bioinformatics and 2-sample Mendelian randomization study

19 Jul 2024

Abstract excerpt

This integrated study combines bioinformatics, machine learning, and Mendelian randomization (MR) to discover and validate molecular biomarkers for sepsis diagnosis. Methods include differential expression analysis, weighted gene co-expression network analysis (WGCNA) for identifying sepsis-related modules and hub genes, and functional enrichment analyses to explore the roles of hub genes. Machine learning...

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PMID: 39029061
DOI: 10.1097/md.0000000000038917

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