princial component analysis (pca) using proc factor Search Results


principle component analysis  (Verlag GmbH)
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Verlag GmbH principle component analysis
Principle Component Analysis, supplied by Verlag GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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principle component analysis  (Tasek Corporation)
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Tasek Corporation principle component analysis
Principle Component Analysis, supplied by Tasek Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pca analysis software  (statpoint inc)
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principle component analyses pca graphs  (MathWorks Inc)
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pearson-type principle component analysis (pca)  (Addinsoft inc)
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principle component analysis  (Umetrics)
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Umetrics principle component analysis
Principle Component Analysis, supplied by Umetrics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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principle component analysis pca  (STATA Corporation)
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STATA Corporation principle component analysis pca
Principle Component Analysis Pca, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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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
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principle component analysis (pca)  (RStudio)
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RStudio principle component analysis (pca)
<t>PCA</t> and ROC reveals the trend of matrix metalloproteinases (MMPs) among multisystem inflammatory syndrome in children (MIS-C), COVID-19 and other groups. (A) <t>Principal</t> <t>component</t> 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.
Principle Component Analysis (Pca), supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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pca plots  (RStudio)
90
RStudio pca plots
<t>PCA</t> and ROC reveals the trend of matrix metalloproteinases (MMPs) among multisystem inflammatory syndrome in children (MIS-C), COVID-19 and other groups. (A) <t>Principal</t> <t>component</t> 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.
Pca Plots, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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statistical excel add-in v. 5.05  (ESUMI Co Ltd)
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ESUMI Co Ltd statistical excel add-in v. 5.05
<t>PCA</t> and ROC reveals the trend of matrix metalloproteinases (MMPs) among multisystem inflammatory syndrome in children (MIS-C), COVID-19 and other groups. (A) <t>Principal</t> <t>component</t> 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.
Statistical Excel Add In V. 5.05, supplied by ESUMI Co Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


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