ArticleClinical medicine insights. Endocrinology and diabetes2023
Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus.
Article in Clinical medicine insights. Endocrinology and diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- The Application of Omics Technologies in Type II Diabetes Mellitus Research.Current diabetes reviews · 2026Review
- From omics to AI-mapping the pathogenic pathways in type 2 diabetes.FEBS letters · 2025Review
- Role of HSP90 in Type 2 Diabetes Mellitus and Its Association with Liver Diseases.Molecular biotechnology · 2025Review
- TUBB4A relieves high glucose-induced cardiomyocyte hypertrophy and apoptosis through the regulation of ubiquitination and activation of the NOTCH signaling pathway.Cytotechnology · 2025Article
- Machine Learning and Augmented Intelligence Enables Prognosis of Type 2 Diabetes Prior to Clinical Manifestation.Current diabetes reviews · 2025Review
- Review
- Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis.Biomedicines · 2023Article
- Human Exome Sequencing and Prospects for Predictive Medicine: Analysis of International Data and Own Experience.Journal of personalized medicine · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Background: Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM. Methods: The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes. Results: A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes Conclusion: The potential crucial genes, especially
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