Fig. 3 | Scientific Reports

Fig. 3

From: Integrated machine learning analysis of proteomic and transcriptomic data identifies healing associated targets in diabetic wound repair

Fig. 3

The microRNA profile in db/db mice wound exudates. Principal Component Analysis of top 500 variable miRNA expression after variance stabilizing transform, colored by Days Post Wounding (DPW) (A). Heatmap of sample to sample Pearson correlation using the top 200 variable microRNAs (B). Volcano plot of Early (DPW 3 and 5) vs Late (DPW 10 and 16) wound healing phases showing differentially expressed genes. Positive Log2 Fold Changes (FC) indicate microRNAs upregulated in the early phase, whereas negative Log2 FC indicate microRNAs upregulated during the late phase (C). DIANA-miRPath v4.0 analysis on top de-regulated microRNAs in Early vs Late phase wound healing, using the collective miRNA targets to identify differentially regulated pathways (D and E). D is downregulated pathway in early and E is upregulated pathway in early. (n = 5 for each timepoint).

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