ArticleInternational journal of molecular sciences2023
Identification of Signature Genes of Dilated Cardiomyopathy Using Integrated Bioinformatics Analysis.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Bioinformatic identification of important roles of COL1A1 and TNFRSF12A in cartilage injury and osteoporosis.Journal of the International Society of Sports Nutrition · 2025Article
- Integrative Approaches to Myopathies and Muscular Dystrophies: Molecular Mechanisms, Diagnostics, and Future Therapies.International journal of molecular sciences · 2025Review
- Novel molecular mechanisms of immune evasion in hepatocellular carcinoma: NSUN2-mediated increase of SOAT2 RNA methylation.Cancer communications (London, England) · 2025Article
- Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation.Journal of biological engineering · 2024Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Dilated cardiomyopathy (DCM) is characterized by left ventricular or biventricular enlargement with systolic dysfunction. To date, the underlying molecular mechanisms of dilated cardiomyopathy pathogenesis have not been fully elucidated, although some insights have been presented. In this study, we combined public database resources and a doxorubicin-induced DCM mouse model to explore the significant genes of DCM in full depth. We first retrieved six DCM-related microarray datasets from the GEO database using several keywords. Then we used the "LIMMA" (linear model for microarray data) R package to filter each microarray for differentially expressed genes (DEGs). Robust rank aggregation (RRA), an extremely robust rank aggregation method based on sequential statistics, was then used to integrate the results of the six microarray datasets to filter out the reliable differential genes. To further improve the reliability of our results, we established a doxorubicin-induced DCM model in C57BL/6N mice, using the "DESeq2" software package to identify DEGs in the sequencing data. We cross-validated the results of RRA analysis with those of animal experiments by taking intersections and identified three key differential genes (including
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Registered trials
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