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principle component factor analysis  (SAS institute)


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    SAS institute principle component factor analysis
    Principle Component Factor Analysis, supplied by SAS institute, 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/principle+component+analysis+function/principle+component+factor+analysis/pmc04990818-223-1-22
    Average 90 stars, based on 1 article reviews
    principle component factor analysis - by Bioz Stars, 2026-11
    90/100 stars

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    other:

    Article Title: Maladaptive choices by defeated rats: link between rapid approach to social threat and escalated cocaine self-administration.
    Article Snippet: A principle component factor analysis was used to determine the relationship between specific behaviors during social defeat stress and subsequent cocaine selfadministration (SAS, SAS Institute).

    Article Title: Maladaptive choices by defeated rats: link between rapid approach to social threat and escalated cocaine self-administration
    Article Snippet: A principle component factor analysis was used to determine the relationship between specific behaviors during social defeat stress and subsequent cocaine self-administration (SAS, SAS Institute).

    Construct:

    Article Title: Managerial Caring Behaviors: Development and Initial Validation of the Model
    Article Snippet: Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform.. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content.. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis.



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    a Heat-map representation of viral gene expression levels (Et value, color scale bar) of 25 viral genes (x axis, infection phase and gene number) at 37 environmental samples, specifying station number and water depth (y axis), arranged by hierarchical clustering. b <t>Principle</t> <t>component</t> analysis <t>(PCA)</t> of the viral expression values for each environmental sample plotted over the axes of 1st component (PC1) vs. 2nd component (PC2). Samples are marked in a blue “+” or a red “x” according to the hierarchical clustering in the heat-map (a). c Coefficient values of viral genes for PC1 (x axis) and PC2 (y axis). The labels “Early” in blue, “Mid” in green, and “Late” in red represent the association of each viral gene to different phases of infection based on transcriptomic analysis [23, 24]. The gene number is depicted according to Supplementary Table S3
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    a Heat-map representation of viral gene expression levels (Et value, color scale bar) of 25 viral genes (x axis, infection phase and gene number) at 37 environmental samples, specifying station number and water depth (y axis), arranged by hierarchical clustering. b Principle component analysis (PCA) of the viral expression values for each environmental sample plotted over the axes of 1st component (PC1) vs. 2nd component (PC2). Samples are marked in a blue “+” or a red “x” according to the hierarchical clustering in the heat-map (a). c Coefficient values of viral genes for PC1 (x axis) and PC2 (y axis). The labels “Early” in blue, “Mid” in green, and “Late” in red represent the association of each viral gene to different phases of infection based on transcriptomic analysis [23, 24]. The gene number is depicted according to Supplementary Table S3

    Journal: The ISME Journal

    Article Title: Expression profiling of host and virus during a coccolithophore bloom provides insights into the role of viral infection in promoting carbon export

    doi: 10.1038/s41396-017-0004-x

    Figure Lengend Snippet: a Heat-map representation of viral gene expression levels (Et value, color scale bar) of 25 viral genes (x axis, infection phase and gene number) at 37 environmental samples, specifying station number and water depth (y axis), arranged by hierarchical clustering. b Principle component analysis (PCA) of the viral expression values for each environmental sample plotted over the axes of 1st component (PC1) vs. 2nd component (PC2). Samples are marked in a blue “+” or a red “x” according to the hierarchical clustering in the heat-map (a). c Coefficient values of viral genes for PC1 (x axis) and PC2 (y axis). The labels “Early” in blue, “Mid” in green, and “Late” in red represent the association of each viral gene to different phases of infection based on transcriptomic analysis [23, 24]. The gene number is depicted according to Supplementary Table S3

    Article Snippet: Principle component analysis was conducted on normalized Et values using the principle component analysis (PCA) function in MATLAB (MathWorks).

    Techniques: Gene Expression, Infection, Environmental Sampling, Expressing