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principle component analysis (pca)  (OriginLab corp)

 
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    OriginLab corp principle component analysis (pca)
    Principle Component Analysis (Pca), supplied by OriginLab corp, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/principle component analysis (pca)/product/OriginLab corp
    Average 90 stars, based on 1 article reviews
    principle component analysis (pca) - by Bioz Stars, 2026-04
    90/100 stars

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    PCA and ROC reveals the trend of matrix metalloproteinases (MMPs) among multisystem inflammatory syndrome in children (MIS-C), COVID-19 and other groups. (A) Principal component analysis (PCA) was performed to show the distribution of data from the combination of five groups: MIS-C (brown), acute COVID-19 (blue), children with other diseases (yellow color), convalescent COVID-19 (green) and control (red) children depicted using normalized data from plasma levels of MMP-8, 12 and 13. (B) CombiROC analysis was performed to determine the role of MMP 8, 12 and 13 in distinguishing between MIS-C vs. acute COVID-19, MIS-C vs. other diseases, MIS-C vs. convalescent and MIS-C vs. Controls.

    Journal: Frontiers in Medicine

    Article Title: Role of matrix metalloproteinases in multi-system inflammatory syndrome and acute COVID-19 in children

    doi: 10.3389/fmed.2022.1050804

    Figure Lengend Snippet: PCA and ROC reveals the trend of matrix metalloproteinases (MMPs) among multisystem inflammatory syndrome in children (MIS-C), COVID-19 and other groups. (A) Principal component analysis (PCA) was performed to show the distribution of data from the combination of five groups: MIS-C (brown), acute COVID-19 (blue), children with other diseases (yellow color), convalescent COVID-19 (green) and control (red) children depicted using normalized data from plasma levels of MMP-8, 12 and 13. (B) CombiROC analysis was performed to determine the role of MMP 8, 12 and 13 in distinguishing between MIS-C vs. acute COVID-19, MIS-C vs. other diseases, MIS-C vs. convalescent and MIS-C vs. Controls.

    Article Snippet: Principle Component Analysis (PCA) was performed to seek linear combinations of the biomarkers that separate out different clusters corresponding to each biomarker that best explain the variance in the data using the R studio.

    Techniques: Control, Clinical Proteomics