Identification of Potential Diagnostic Gene Targets for Pediatric Sepsis Based on Bioinformatics and Machine Learning

Identification of Potential Diagnostic Gene Targets for Pediatric Sepsis Based on Bioinformatics and Machine Learning

Purpose: To develop a comprehensive differential expression gene profile as well as a prediction model based on the expression analysis of pediatric sepsis specimens.Methods: In this study, compared with control specimens, a total of 708 differentially expressed genes in pediatric sepsis (case–contr...

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Bibliographic Details
Main Authors: Ying Qiao, Bo Zhang, Ying Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Pediatrics
Subjects:
sepsis
pediatric sepsis
GO enrichment analysis
KEGG enrichment analysis
logistic regression model
biomarker
Online Access:https://www.frontiersin.org/articles/10.3389/fped.2021.576585/full

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