Article

Multiple datasets to explore the molecular mechanism of sepsis

2022-04-12

Abstract excerpt

<h4>Background: </h4> This study aimed to identify potential biomarkers, by means of bioinformatics, affecting the occurrence and development of septic shock. <h4>Methods: </h4>: The self-test data and differential genes in GSE131761 were screened, and the diagnostic model of sepsis was further constructed by Lasso regression to identify key genes. The stability of the model was verified by ROC curve. Finally, imm...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 5a3ccc00-c057-54ff-9f44-3a8ed698aa53
DOI: 10.21203/rs.3.rs-1453819/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Multiple datasets to explore the molecular mechanism of sepsisDOI 10.21203/rs.3.rs-1453819/v1Read

exploring the molecular mechanism of sepsis comprehensively based on multi-omics analysisSemantic proximity Read

A Meta-Analysis of Whole Blood Transcriptome Reveals Association of Increased Neutrophil Activity and T cell Suppression in SepsisSemantic proximity Read

Comprehensive Analysis of Molecular Subtypes and Hub Genes of Sepsis by Gene Expression ProfilesSemantic proximity Read

Screening of Key Genes of Sepsis and Septic Shock Using Bioinformatics AnalysisSemantic proximity Read

Integrated analysis of multi-omics data reveals T cell exhaustion in sepsisSemantic proximity Read

Bioinformatics Analysis for Multiple Gene Expression Profiles in SepsisSemantic proximity Read

Analysis of novel biomarkers and immune cell alterations in sepsis based on single-cell sequencing and machine learning algorithmsSemantic proximity Read

Identification of potential diagnostic and prognostic biomarkers for sepsis based on machine learningSemantic proximity Read

Bioinformatics-based screening of sepsis biomarkersSemantic proximity Read

Predicting the prognosis in patients with sepsis by a pyroptosis-related gene signatureSemantic proximity Read

Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus databaseSemantic proximity Read

Bioinformatics and next generation data analysis reveals the potential role of inflammation in sepsis and its associated complicationsSemantic proximity Read