Article

Revealing the novel pyroptosis-related therapeutic targets for sepsis based on the machine learning

2022-10-17

Abstract excerpt

<h4>Background: </h4> Sepsis is one of the most lethal diseases worldwide. Pyroptosis as a unique form of cell death and the mechanism of interaction with sepsis is not yet clear. The aim of this study is to uncover pyroptosis genes associated with sepsis and to provide early therapeutic targets for the treatments of sepsis. Methods Based on the GSE134347 dataset, sepsis-related genes were mined by differential e...

Topics

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

Identifiers and source

Literature Corpus work: 03631265-8068-571a-88d5-7406d7d8ff90
DOI: 10.21203/rs.3.rs-2145292/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Revealing the novel pyroptosis-related therapeutic targets for sepsis based on the machine learningDOI 10.21203/rs.3.rs-2145292/v1Read

Revealing novel pyroptosis-related therapeutic targets for sepsis based on machine learningSemantic proximity Read

Pyroptosis-related gene signature in neutrophils for predicting the prognosis of sepsisSemantic proximity Read

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

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

Bioinformatics-based screening of sepsis biomarkersSemantic proximity Read

Identification of ferroptosis-related key genes associated with immune infiltration in sepsis by bioinformatics analysis and in vivo validationSemantic proximity Read

Exploring the Role of Different Cell-Death-Related Genes in Sepsis Diagnosis Using a Machine Learning AlgorithmSemantic proximity Read

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

Identification of common core genes and pathways of sepsis and cancer by bioinformatics analysisSemantic proximity Read

Identification of immune-related endoplasmic reticulum stress genes in sepsis using bioinformatics and machine learningSemantic proximity Read

Construction of gene network database, and identification of key genes for diagnosis, prognosis, and treatment in sepsisSemantic proximity Read

Bioinformatics analysis to screen for critical genes between survived and non‑survived patients with sepsisSemantic proximity Read