Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
August 18, 2025PLoS ONEOpen Access

Integrating bioinformatics and machine learning to elucidate the role of protein glycosylation-related genes in the pathogenesis of diabetic kidney disease

View Full Paper
Ask AI
Bookmark
Share

Authors

ZLZiyang LiuZQZhenkui QinWBWenxin Bai

Discussion

Loading...

Member takes

Overview

This research reveals diagnostic biomarkers and highlights the role of gene expression and glycosylation in diabetic kidney disease pathogenesis.

Key Points

  • Protein glycosylation is identified as a key player in the pathogenesis of diabetic kidney disease, showing its critical role.
  • Six hub genes relevant to diabetic kidney disease were uncovered through machine learning techniques, indicating their potential as diagnostic markers.
  • Integrated bioinformatics and machine learning analysis of gene expression datasets revealed distinct molecular subtypes of diabetic kidney disease.
  • Immune infiltration analysis indicates significant differences in macrophage and neutrophil activity between patients with diabetic kidney disease and healthy controls.

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/68af2d89cf1dd9ea359e5f73https://doi.org/10.1371/journal.pone.0329640
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Investigating the metabolic reprogramming mechanisms in diabetic nephropathy: a comprehensive analysis using bioinformatics and machine learning2025 · 1 citations
  2. 2Unveiling urinary diagnostic biomarkers for diabetic kidney disease using metabolomics and machine learning approaches2025 · 5 citations
  3. 3Aging-driven transcriptional programs in diabetic kidney disease: multi-omics discovery of diagnostic biomarkers and drug-repurposing targets2026
  4. 4A Metabolomics-Guided Machine Learning Model for Diagnosis and Differential Diagnosis of Diabetic Kidney Disease: A Dual-Center Study2025
  5. 5Genomic mapping of diabetic kidney disease biomarkers and identification of potential inhibitors through virtual screening2025