کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9743526 | 1491193 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Analysis of variance-principal component analysis: A soft tool for proteomic discovery
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
A soft tool for detection of biomarkers in high dimensional data sets has been developed. The tool combines analysis of variance (ANOVA) and principal component analysis (PCA). Covariations are separated using ANOVA into main effects and interaction. The covariances for each effect are combined with the pure error and subjected to PCA. If the main effect is significant compared to the residual error, the first principal component will span this source of variation. This technique avoids rotation of the principal components and when significant the variable loadings are amenable to interpretation. ANOVA-PCA is demonstrated as a tool for optimization of a proteomic assay for biomarkers. Two independent sets of matrix assisted laser desorption/ionization-mass spectra (MALDI-MS) were collected from amniotic fluids. These studies gave consistent biomarkers for premature delivery.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Analytica Chimica Acta - Volume 544, Issues 1â2, 15 July 2005, Pages 118-127
Journal: Analytica Chimica Acta - Volume 544, Issues 1â2, 15 July 2005, Pages 118-127
نویسندگان
Peter de B. Harrington, Nancy E. Vieira, Jimmy Espinoza, Jyh Kae Nien, Roberto Romero, Alfred L. Yergey,