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dendrogram function  (MathWorks Inc)


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    MathWorks Inc dendrogram function
    Example <t>dendrogram</t> for frequency band definition using hierarchical clustering Hierarchical clustering dendrogram derived from PFC ECoG signals. Frequency bins (y-axis) are grouped by the similarity of their temporal power profiles, measured by correlation distance (x-axis; smaller distance indicates higher similarity). Branch colors are visual aids automatically assigned by MATLAB. Brackets and labels illustrate an example of manually defined frequency bands (e.g., Theta, Alpha, Beta sub-bands, Gamma) resulting from user interpretation of the clustering structure. See also .
    Dendrogram Function, supplied by MathWorks Inc, 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/dendrogram/pmc12171811-190-2-5
    Average 90 stars, based on 1 article reviews
    dendrogram function - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Protocol for assisting frequency band definition and decoding neural dynamics using hierarchical clustering and multivariate pattern analysis"

    Article Title: Protocol for assisting frequency band definition and decoding neural dynamics using hierarchical clustering and multivariate pattern analysis

    Journal: STAR Protocols

    doi: 10.1016/j.xpro.2025.103870

    Example dendrogram for frequency band definition using hierarchical clustering Hierarchical clustering dendrogram derived from PFC ECoG signals. Frequency bins (y-axis) are grouped by the similarity of their temporal power profiles, measured by correlation distance (x-axis; smaller distance indicates higher similarity). Branch colors are visual aids automatically assigned by MATLAB. Brackets and labels illustrate an example of manually defined frequency bands (e.g., Theta, Alpha, Beta sub-bands, Gamma) resulting from user interpretation of the clustering structure. See also .
    Figure Legend Snippet: Example dendrogram for frequency band definition using hierarchical clustering Hierarchical clustering dendrogram derived from PFC ECoG signals. Frequency bins (y-axis) are grouped by the similarity of their temporal power profiles, measured by correlation distance (x-axis; smaller distance indicates higher similarity). Branch colors are visual aids automatically assigned by MATLAB. Brackets and labels illustrate an example of manually defined frequency bands (e.g., Theta, Alpha, Beta sub-bands, Gamma) resulting from user interpretation of the clustering structure. See also .

    Techniques Used: Derivative Assay

    Visualization of conventional and hierarchically derived frequency band boundaries on the average TFR (A) The average TFR of normalized ECoG power in the PFC is shown in both panels (color indicates normalized power). Overlaid horizontal dashed lines illustrate different frequency band definitions: the left panel depicts conventional band boundaries, while the right panel shows example boundaries derived from hierarchical clustering. (B) The hierarchical clustering dendrogram (same as ) is shown alongside for reference to the bands used in panel (A), right.
    Figure Legend Snippet: Visualization of conventional and hierarchically derived frequency band boundaries on the average TFR (A) The average TFR of normalized ECoG power in the PFC is shown in both panels (color indicates normalized power). Overlaid horizontal dashed lines illustrate different frequency band definitions: the left panel depicts conventional band boundaries, while the right panel shows example boundaries derived from hierarchical clustering. (B) The hierarchical clustering dendrogram (same as ) is shown alongside for reference to the bands used in panel (A), right.

    Techniques Used: Derivative Assay

    Related Articles

    other:

    Article Title: Multistep diversification in spatiotemporal bacterial-phage coevolution
    Article Snippet: Finally, the cross-infection matrix columns were ordered and the dendrogram was visualized with the MATLAB dendrogram function.

    Article Title: Multistep diversification in spatiotemporal bacterial-phage coevolution.
    Article Snippet: Finally, the cross-infectionmatrix columns were ordered and the dendrogram was visualized with the MATLAB dendrogram function.

    Article Title: Hippocampal conjunctive and complementary CA1 populations relate sensory events to movement
    Article Snippet: Clusters were then separated (color coded in figures using the MATLAB function “dendrogram”) by using a threshold of 70% (default value in dendrogram function) of the maximum linkage distance between any two clusters.

    Generated:

    Article Title: Identification of neural oscillations and epileptiform changes in human brain organoids
    Article Snippet: Following generation of the correlation matrix, linkage analysis was performed using the MATLAB linkage function from the statistics toolbox (with ‘complete’/furthest distance). .. The generated hierarchical clustering was input into the dendrogram function from the MATLAB statistics toolbox with ‘Color Threshold’ fixed at 1.5 for all experimental groups. ..



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    Example <t>dendrogram</t> for frequency band definition using hierarchical clustering Hierarchical clustering dendrogram derived from PFC ECoG signals. Frequency bins (y-axis) are grouped by the similarity of their temporal power profiles, measured by correlation distance (x-axis; smaller distance indicates higher similarity). Branch colors are visual aids automatically assigned by MATLAB. Brackets and labels illustrate an example of manually defined frequency bands (e.g., Theta, Alpha, Beta sub-bands, Gamma) resulting from user interpretation of the clustering structure. See also .
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    Image Search Results


    Interaction map among single-nucleotide polymorphisms (SNPs) of genes on the risk of Acute lymphoblastic leukemia (ALL). Hierarchical clustering dendrogram (a) and Kamada-Kawai (b).

    Journal: Global Medical Genetics

    Article Title: Genetic susceptibility of IKZF1 , ARID5B , and CEBPE polymorphisms to childhood acute lymphoblastic leukemia in Chinese populations: a case-control study

    doi: 10.1016/j.gmg.2025.100084

    Figure Lengend Snippet: Interaction map among single-nucleotide polymorphisms (SNPs) of genes on the risk of Acute lymphoblastic leukemia (ALL). Hierarchical clustering dendrogram (a) and Kamada-Kawai (b).

    Article Snippet: Hierarchical clustering dendrogram (a) and Kamada-Kawai (b).

    Techniques:

    Example dendrogram for frequency band definition using hierarchical clustering Hierarchical clustering dendrogram derived from PFC ECoG signals. Frequency bins (y-axis) are grouped by the similarity of their temporal power profiles, measured by correlation distance (x-axis; smaller distance indicates higher similarity). Branch colors are visual aids automatically assigned by MATLAB. Brackets and labels illustrate an example of manually defined frequency bands (e.g., Theta, Alpha, Beta sub-bands, Gamma) resulting from user interpretation of the clustering structure. See also .

    Journal: STAR Protocols

    Article Title: Protocol for assisting frequency band definition and decoding neural dynamics using hierarchical clustering and multivariate pattern analysis

    doi: 10.1016/j.xpro.2025.103870

    Figure Lengend Snippet: Example dendrogram for frequency band definition using hierarchical clustering Hierarchical clustering dendrogram derived from PFC ECoG signals. Frequency bins (y-axis) are grouped by the similarity of their temporal power profiles, measured by correlation distance (x-axis; smaller distance indicates higher similarity). Branch colors are visual aids automatically assigned by MATLAB. Brackets and labels illustrate an example of manually defined frequency bands (e.g., Theta, Alpha, Beta sub-bands, Gamma) resulting from user interpretation of the clustering structure. See also .

    Article Snippet: Note: The dendrogram function in MATLAB automatically assigns colors to different branches based on the cluster hierarchy and the specified `ColorThreshold` parameter (default 0.5, adjustable by the user).

    Techniques: Derivative Assay

    Visualization of conventional and hierarchically derived frequency band boundaries on the average TFR (A) The average TFR of normalized ECoG power in the PFC is shown in both panels (color indicates normalized power). Overlaid horizontal dashed lines illustrate different frequency band definitions: the left panel depicts conventional band boundaries, while the right panel shows example boundaries derived from hierarchical clustering. (B) The hierarchical clustering dendrogram (same as ) is shown alongside for reference to the bands used in panel (A), right.

    Journal: STAR Protocols

    Article Title: Protocol for assisting frequency band definition and decoding neural dynamics using hierarchical clustering and multivariate pattern analysis

    doi: 10.1016/j.xpro.2025.103870

    Figure Lengend Snippet: Visualization of conventional and hierarchically derived frequency band boundaries on the average TFR (A) The average TFR of normalized ECoG power in the PFC is shown in both panels (color indicates normalized power). Overlaid horizontal dashed lines illustrate different frequency band definitions: the left panel depicts conventional band boundaries, while the right panel shows example boundaries derived from hierarchical clustering. (B) The hierarchical clustering dendrogram (same as ) is shown alongside for reference to the bands used in panel (A), right.

    Article Snippet: Note: The dendrogram function in MATLAB automatically assigns colors to different branches based on the cluster hierarchy and the specified `ColorThreshold` parameter (default 0.5, adjustable by the user).

    Techniques: Derivative Assay