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orthogonal partial least square (opls) algorithm  (Umetrics)

 
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    Structured Review

    Umetrics orthogonal partial least square (opls) algorithm
    Validation of predictive models for PDB severity scores. Orthogonal Partial Least Square <t>(OPLS)</t> classifier was trained on the discover set and tested on the cross-validation set. The features consisted of the list of significant sites from site and region level analysis based on the discovery samples (Panels A and C, n = 2,247 CpG sites) and separately, on a best explanatory subset from this pool of sites obtained with the Glmnet (Panels B and D, n = 33 CpG sites) (A,B) Scatter plots of predicted versus observed PDB_severity scores for each model. The observed PDB severity scores were also dichotomized into two groups based on the median PDB severity score of seven; low severity (PDB_severity_score <7; blue) and high severity (PDB_severity_score ≥7; red) and subsequently used for ROC curve analysis showing the area under curve AUC for pooled sites (C) and Glmnet selected sites (D) .
    Orthogonal Partial Least Square (Opls) Algorithm, supplied by Umetrics, 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/product/partial+least-squares+algorithm/simca+13/pmc09235511-128-4-10
    Average 90 stars, based on 1 article reviews
    orthogonal partial least square (opls) algorithm - by Bioz Stars, 2026-09
    90/100 stars

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    1) Product Images from "Epigenetic DNA Methylation Signatures Associated With the Severity of Paget’s Disease of Bone"

    Article Title: Epigenetic DNA Methylation Signatures Associated With the Severity of Paget’s Disease of Bone

    Journal: Frontiers in Cell and Developmental Biology

    doi: 10.3389/fcell.2022.903612

    Validation of predictive models for PDB severity scores. Orthogonal Partial Least Square (OPLS) classifier was trained on the discover set and tested on the cross-validation set. The features consisted of the list of significant sites from site and region level analysis based on the discovery samples (Panels A and C, n = 2,247 CpG sites) and separately, on a best explanatory subset from this pool of sites obtained with the Glmnet (Panels B and D, n = 33 CpG sites) (A,B) Scatter plots of predicted versus observed PDB_severity scores for each model. The observed PDB severity scores were also dichotomized into two groups based on the median PDB severity score of seven; low severity (PDB_severity_score <7; blue) and high severity (PDB_severity_score ≥7; red) and subsequently used for ROC curve analysis showing the area under curve AUC for pooled sites (C) and Glmnet selected sites (D) .
    Figure Legend Snippet: Validation of predictive models for PDB severity scores. Orthogonal Partial Least Square (OPLS) classifier was trained on the discover set and tested on the cross-validation set. The features consisted of the list of significant sites from site and region level analysis based on the discovery samples (Panels A and C, n = 2,247 CpG sites) and separately, on a best explanatory subset from this pool of sites obtained with the Glmnet (Panels B and D, n = 33 CpG sites) (A,B) Scatter plots of predicted versus observed PDB_severity scores for each model. The observed PDB severity scores were also dichotomized into two groups based on the median PDB severity score of seven; low severity (PDB_severity_score <7; blue) and high severity (PDB_severity_score ≥7; red) and subsequently used for ROC curve analysis showing the area under curve AUC for pooled sites (C) and Glmnet selected sites (D) .

    Techniques Used: Biomarker Discovery

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    Article Title: Influence of Different Shaping Techniques on the Aroma Quality and Volatile Metabolites of Green Tea Revealed by Gas Chromatography Electronic Nose and Gas Chromatography-Tandem Mass Spectrometry.
    Article Snippet: Partial least squares discrimination analysis (PLS-DA) was implemented via the application of SIMCA-P 13.0 (Umetrics, Umea, Sweden).

    Article Title: Impact of Combined Macronutrient Diet on Amino Acids and Amines Plasma Levels.
    Article Snippet: Subsequently, outliers identified using principal components analysis (PCA) were removed to construct Partial Least Squares Discriminant Analysis (PLS-DA) models using Umetrics SIMCA 18 software (v. 18.0.0.372).

    Article Title: Variety-specific flavor characteristics in the Shandong region: Interaction between fermentation and variety.
    Article Snippet: Exploring new grape varieties in a specific wine region helps enhance product style diversity.. This study investigated the flavor characteristics of Cabernet Sauvignon, Merlot, Dornfelder, and Refosco grapes and their wines in the Shandong region, focusing on how fermentation interacts with these varieties to shape their profiles.. Results showed that Dornfelder grapes exhibited significantly higher levels of 26 aroma compounds than other varieties, with total aroma compound concentrations 1.75 to 2.38 times greater.

    Article Title: Inflammation and metabolic dysfunction underly anhedonia-like behavior in antidepressant resistant male rats.
    Article Snippet: To identify the variables that differ most between the control and ACTH treatments, supervised analysis using partial least squares-discriminant analysis (PLSDA) was performed using Simca v17 (Umetrics, Sartorius).

    Article Title: Metabolic markers detect early ostedifferentiation of mesenchymal stem cells from multiple donors.
    Article Snippet: Multivariate analysis (MVA) included principal component analysis (PCA) and partial-least-squares discriminant analysis (PLS-DA) (SIMCA-P 11.5, Umetrics, Umeå, Sweden) were used on either full resolution 1H NMR spectra or selected signal integrals.

    Gas Chromatography-Mass Spectrometry:

    Article Title: Influence of Aging Technologies on the Volatile Profile Composition of Carignano cv Red Wines in Sardinia.
    Article Snippet: .. GC-MS datasets were imported into SIMCA 13 (Umetrics AB, Umea, Sweden) for processing principal component analysis (PCA). ..



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    Umetrics orthogonal partial least square (opls) algorithm
    Validation of predictive models for PDB severity scores. Orthogonal Partial Least Square <t>(OPLS)</t> classifier was trained on the discover set and tested on the cross-validation set. The features consisted of the list of significant sites from site and region level analysis based on the discovery samples (Panels A and C, n = 2,247 CpG sites) and separately, on a best explanatory subset from this pool of sites obtained with the Glmnet (Panels B and D, n = 33 CpG sites) (A,B) Scatter plots of predicted versus observed PDB_severity scores for each model. The observed PDB severity scores were also dichotomized into two groups based on the median PDB severity score of seven; low severity (PDB_severity_score <7; blue) and high severity (PDB_severity_score ≥7; red) and subsequently used for ROC curve analysis showing the area under curve AUC for pooled sites (C) and Glmnet selected sites (D) .
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    Image Search Results


    Validation of predictive models for PDB severity scores. Orthogonal Partial Least Square (OPLS) classifier was trained on the discover set and tested on the cross-validation set. The features consisted of the list of significant sites from site and region level analysis based on the discovery samples (Panels A and C, n = 2,247 CpG sites) and separately, on a best explanatory subset from this pool of sites obtained with the Glmnet (Panels B and D, n = 33 CpG sites) (A,B) Scatter plots of predicted versus observed PDB_severity scores for each model. The observed PDB severity scores were also dichotomized into two groups based on the median PDB severity score of seven; low severity (PDB_severity_score <7; blue) and high severity (PDB_severity_score ≥7; red) and subsequently used for ROC curve analysis showing the area under curve AUC for pooled sites (C) and Glmnet selected sites (D) .

    Journal: Frontiers in Cell and Developmental Biology

    Article Title: Epigenetic DNA Methylation Signatures Associated With the Severity of Paget’s Disease of Bone

    doi: 10.3389/fcell.2022.903612

    Figure Lengend Snippet: Validation of predictive models for PDB severity scores. Orthogonal Partial Least Square (OPLS) classifier was trained on the discover set and tested on the cross-validation set. The features consisted of the list of significant sites from site and region level analysis based on the discovery samples (Panels A and C, n = 2,247 CpG sites) and separately, on a best explanatory subset from this pool of sites obtained with the Glmnet (Panels B and D, n = 33 CpG sites) (A,B) Scatter plots of predicted versus observed PDB_severity scores for each model. The observed PDB severity scores were also dichotomized into two groups based on the median PDB severity score of seven; low severity (PDB_severity_score <7; blue) and high severity (PDB_severity_score ≥7; red) and subsequently used for ROC curve analysis showing the area under curve AUC for pooled sites (C) and Glmnet selected sites (D) .

    Article Snippet: The Orthogonal Partial Least Square (OPLS) algorithm by SIMCA ver.15 (Umetrics, Sweden) was used to construct predictive models.

    Techniques: Biomarker Discovery