ArticleExperimental and therapeutic medicine2016
Establishment of a prediction model of changing trends in cardiac hypertrophy disease based on microarray data screening.
Article in Experimental and therapeutic medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Weighted gene co-expression network-based approach to identify key genes associated with anthracycline-induced cardiotoxicity and construction of miRNA-transcription factor-gene regulatory network.Molecular medicine (Cambridge, Mass.) · 2021Article
- Cardiomyocyte glucocorticoid and mineralocorticoid receptors directly and antagonistically regulate heart disease in mice.Science signaling · 2019Article
- Article
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8 authors.
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Abstract
The aim of the present study was to construct a mathematical model to predict the changing trends of cardiac hypertrophy at gene level. Microarray data were downloaded from Gene Expression Omnibus database (accession, GSE21600), which included 35 samples harvested from the heart of Wistar rats on postoperative days 1 (D1 group), 6 (D6 group) and 42 (D42 group) following aorta ligation and sham operated Wistar rats, respectively. Each group contained six samples, with the exception of the samples harvested from the aorta ligated group after 6 days, where n=5. Differentially expressed genes (DEGs) were identified using a Limma package in R. Hierarchical clustering analysis was performed on common DEGs in order to construct a linear equation between the D1 and D42 groups, using linear discriminant analysis. Subsequent verification was performed using receiver operating characteristic (ROC) curve and the measurement data at day 42. A total of 319, 44 and 57 DEGs were detected in D1, D6 and D42 sample groups, respectively.
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