Combination of machine learning and protein-protein interaction network established one ATM-DPP4-TXN ferroptotic diagnostic model with experimental validation

Ferroptosis and lethal sepsis are interlinked, although this association remains largely unknown to clinical panels. Sepsis is characterized by dysfunction of the inflammatory microenvironment. Most septic biomarkers lack independent validation, and a comprehensive diagnosis comprising biomarker ass...

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Bibliographic Details
Published in:	Molecular medicine reports Vol. 32; no. 3; pp. 1 - 20
Main Authors:	Wu, Mengze, Zou, Zhao, Peng, Yuce, Luo, Suxin
Format:	Journal Article
Language:	English
Published:	Greece D.A. Spandidos 01.09.2025 Spandidos Publications Spandidos Publications UK Ltd
Subjects:	Algorithms Ataxia telangiectasia ataxia telangiectasia mutated Ataxia telangiectasia mutated protein Ataxia Telangiectasia Mutated Proteins - genetics Ataxia Telangiectasia Mutated Proteins - metabolism Bioinformatics Biomarkers Cell death Computational Biology - methods Databases, Genetic Datasets Diagnosis Dipeptidyl Peptidase 4 DPP4 Enzymes Ferroptosis Ferroptosis - genetics Gene expression Gene Expression Profiling Gene Regulatory Networks Gene set enrichment analysis Genetic aspects Genomes Health aspects Humans immune microenvironment Immune response Inflammation Kidneys Learning algorithms Machine Learning Medical research Medicine, Experimental Nomograms Oxidative stress Protein interaction Protein Interaction Maps Protein-protein interactions Proteins Regression analysis Sepsis Sepsis - diagnosis Sepsis - genetics Sepsis - metabolism Support vector machines Thioredoxin Thioredoxins - genetics Thioredoxins - metabolism China DPP4 ataxia telangiectasia mutated ferroptosis immune microenvironment thioredoxin sepsis
ISSN:	1791-2997, 1791-3004, 1791-3004
Online Access:	Get full text
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