Back to search

Article

Identification of Lipid Metabolism-Related Genes in Rheumatoid Arthritis Using Bioinformatics and Machine Learning

2025-11-06

Abstract excerpt

<title>Abstract</title> <p> <bold>Background</bold> Rheumatoid arthritis (RA) is a common autoimmune inflammatory joint disease. Recent studies suggest that lipid metabolism dysregulation plays a crucial role in RA pathogenesis; however, its precise mechanisms remain unclear. This study aims to identify lipid metabolism-related diagnostic biomarkers in RA and analyze their potential pathogenic mechanisms and cl...

Topics

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

Identifiers and source

Literature Corpus work
2fe6fb87-c725-5946-894f-a763a71f0769
DOI
10.21203/rs.3.rs-7913208/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Identification of Lipid Metabolism-Related Genes in Rheumatoid Arthritis Using Bioinformatics and Machine LearningDOI 10.21203/rs.3.rs-7913208/v1
Identification of key genes and immune profile in rheumatoid arthritis by bioinformatics analysisSemantic proximity
Identification of Key Immune-Related Genes, Molecular Pathways and Immune Infiltration as Diagnostic and Therapeutic Candidate Targets for RA: an integrated bioinformatics-based analysisSemantic proximity
Identification of immune-related genes in diagnosing atherosclerosis with rheumatoid arthritis through bioinformatics analysis and machine learningSemantic proximity
Identification of mitophagy-related biomarkers in human rheumatoid arthritis using machine learning modelsSemantic proximity
Machine learning and weighted gene co-expression network analysis identify a three-gene signature to diagnose rheumatoid arthritisSemantic proximity
Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysisSemantic proximity
Identification of three-gene signature to diagnose rheumatoid arthritis through WGCNA and machine learning methodsSemantic proximity
An overview of multi-omics technologies in rheumatoid arthritis: applications in biomarker and pathway discoverySemantic proximity
CD3D, GZMK, and KLRB1 Are Potential Markers for Early Diagnosis of Rheumatoid Arthritis, Especially in Anti-Citrullinated Protein Antibody-Negative PatientsSemantic proximity
Identification of novel targets associated with cholesterol metabolism in nonalcoholic fatty liver disease: a comprehensive study using Mendelian randomization combined with transcriptome analysisSemantic proximity
Machine learning-based identification of key lipid metabolism-related genes and associated ceRNA networks in NAFLDSemantic proximity
Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysisSemantic proximity
Select a neighboring publication to make it the new centre.