ArticleJournal of thoracic disease2025
Bioinformatics-based screening of genes associated with dilated cardiomyopathy.
Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Identification of a Lactylation-Related Gene Signature and Candidate Biomarkers for Dilated Cardiomyopathy.Journal of cellular and molecular medicine · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Due to the lack of appropriate diagnostic biomarkers and intervention targets, the diagnosis and treatment of dilated cardiomyopathy (DCM) in clinical practice are considerably challenging. Therefore, this study aimed to identify reliable biomarker genes using bioinformatics methods to improve the clinical management of DCM. Methods: Three DCM gene datasets, GSE120895, GSE42955, and GSE3586, were downloaded from the Gene Expression Omnibus (GEO). Differential gene analysis was used to screen for differentially expressed genes in these datasets, and weighted gene coexpression network analysis (WGCNA) was used to screen for the gene coexpression modules most relevant to DCM. Machine learning algorithms and a Protein-protein interaction (PPI) network were used to screen for the core DCM genes in the gene coexpression module. Results: WGCNA identified the turquoise module as the most relevant gene module for DCM disease. Subsequently, machine learning algorithms identified 8 core genes while PPI screening identified 10 core genes. Conclusions: In this study, the
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