• 03:17 1.
    Decide Which Genes are Significantly Regulated ?
  • 06:57 2.
    Decide Which Genes are Significantly Regulated ?
  • 03:07 3.
    Decide Which Genes are Significantly Regulated ?
  • 03:37 4.
    Decide Which Genes are Significantly Regulated ?
  • 03:57 5.
    Statistical Distribution
  • 06:01 6.
    Decide Which Genes are Significantly Regulated ?
  • 02:45 7.
    Question
  • 05:40 8.
    Decide which genes are significantly regulated ?3
  • 01:48 9.
    Permutation test
  • 00:38 10.
    QuestionWhat is F-test? Mann–Whitney tests Kruskal–Wallis tests Analysis of Variance Permutation test
  • 05:29 11.
    Concept of Biostatistics About Nominal (Categorical) Variable
  • 02:27 12.
    Concept of Biostatistics About Nominal Variable
  • 01:46 13.
    Survival Analysis
  • 04:37 14.
    Univariate Method: Kaplan-Meier Survival Curves
  • 01:09 15.
    Web Tool: Kaplan-Meier Plotter
  • 02:09 16.
    Multivariate Method: Cox Proportional Hazards
  • 01:46 17.
    Summary
  • 08:07 18.
    Clustering Analysis
  • 02:19 19.
    Distances Between Clusters Used For Hierarchical Clustering
  • 02:40 20.
    Algorithm: deterministic (top-down: divisive; bottom-up: agglomerative) Compute distance matrix for all pairs of nodes (genes); Find two closest nodes Merge them into a new node with some joining method Compute distance of new node to all other nodes Rep
  • 01:52 21.
    Hierarchical Clustering1
  • 02:44 22.
    Hierarchical Clustering2
  • 04:46 23.
    Partitional Algorithms: K-means / K-medians
  • 01:15 24.
    Partitional Algorithms: K-means / K-medians
  • 01:04 25.
    Partitional Algorithms: Self-Organizing Map Algorithm
  • 00:31 26.
    Artificial Neural Network
  • 01:34 27.
    The SOM Algorithm - A Summary of Steps1
  • 00:41 28.
    The SOM Algorithm - A Summary of Steps2
  • 01:46 29.
    The SOM Algorithm - A Summary of Steps3
  • 01:01 30.
    The SOM Algorithm - A Summary of Steps5
  • 01:51 31.
    Supervised Algorithm
  • 00:51 32.
    Support Vector Machine
  • 00:46 33.
    K-Nearest Neighbor (K-NN)
  • 02:16 34.
    Decision Trees / Random Forest
  • Index
  • Notes
  • Comment
  • Fullscreen
Comparative Gene-Expression Analysis I: Hybridization-based techniques (0316)
Duration: 1:33:29, Browse: 342, Last Updated: 2021-03-16
    Prev Next
    • 03:17 1.
      Decide Which Genes are Significantly Regulated ?
    • 06:57 2.
      Decide Which Genes are Significantly Regulated ?
    • 03:07 3.
      Decide Which Genes are Significantly Regulated ?
    • 03:37 4.
      Decide Which Genes are Significantly Regulated ?
    • 03:57 5.
      Statistical Distribution
    • 06:01 6.
      Decide Which Genes are Significantly Regulated ?
    • 02:45 7.
      Question
    • 05:40 8.
      Decide which genes are significantly regulated ?3
    • 01:48 9.
      Permutation test
    • 00:38 10.
      QuestionWhat is F-test? Mann–Whitney tests Kruskal–Wallis tests Analysis of Variance Permutation test
    • 05:29 11.
      Concept of Biostatistics About Nominal (Categorical) Variable
    • 02:27 12.
      Concept of Biostatistics About Nominal Variable
    • 01:46 13.
      Survival Analysis
    • 04:37 14.
      Univariate Method: Kaplan-Meier Survival Curves
    • 01:09 15.
      Web Tool: Kaplan-Meier Plotter
    • 02:09 16.
      Multivariate Method: Cox Proportional Hazards
    • 01:46 17.
      Summary
    • 08:07 18.
      Clustering Analysis
    • 02:19 19.
      Distances Between Clusters Used For Hierarchical Clustering
    • 02:40 20.
      Algorithm: deterministic (top-down: divisive; bottom-up: agglomerative) Compute distance matrix for all pairs of nodes (genes); Find two closest nodes Merge them into a new node with some joining method Compute distance of new node to all other nodes Rep
    • 01:52 21.
      Hierarchical Clustering1
    • 02:44 22.
      Hierarchical Clustering2
    • 04:46 23.
      Partitional Algorithms: K-means / K-medians
    • 01:15 24.
      Partitional Algorithms: K-means / K-medians
    • 01:04 25.
      Partitional Algorithms: Self-Organizing Map Algorithm
    • 00:31 26.
      Artificial Neural Network
    • 01:34 27.
      The SOM Algorithm - A Summary of Steps1
    • 00:41 28.
      The SOM Algorithm - A Summary of Steps2
    • 01:46 29.
      The SOM Algorithm - A Summary of Steps3
    • 01:01 30.
      The SOM Algorithm - A Summary of Steps5
    • 01:51 31.
      Supervised Algorithm
    • 00:51 32.
      Support Vector Machine
    • 00:46 33.
      K-Nearest Neighbor (K-NN)
    • 02:16 34.
      Decision Trees / Random Forest
    Location
    1. Media Center
    2. ...
    3. 2021
    Folder name
    2021
    Author
    賴亮全
    Branch
    賴亮全教授
    Created
    2021-03-16 16:14:25
    Last Updated
    2021-03-16 22:36:52
    Browse
    342
    Duration
    1:33:29