• 00:00 1.
    Decide Which Genes are Significantly Regulated ?
  • 03:17 2.
    Decide Which Genes are Significantly Regulated ?
  • 10:14 3.
    Decide Which Genes are Significantly Regulated ?
  • 13:21 4.
    Decide Which Genes are Significantly Regulated ?
  • 16:59 5.
    Statistical Distribution
  • 20:56 6.
    Decide Which Genes are Significantly Regulated ?
  • 26:57 7.
    Question
  • 29:43 8.
    Decide which genes are significantly regulated ?3
  • 35:23 9.
    Permutation test
  • 37:12 10.
    QuestionWhat is F-test? Mann–Whitney tests Kruskal–Wallis tests Analysis of Variance Permutation test
  • 37:50 11.
    Concept of Biostatistics About Nominal (Categorical) Variable
  • 43:20 12.
    Concept of Biostatistics About Nominal Variable
  • 45:47 13.
    Survival Analysis
  • 47:33 14.
    Univariate Method: Kaplan-Meier Survival Curves
  • 52:11 15.
    Web Tool: Kaplan-Meier Plotter
  • 53:20 16.
    Multivariate Method: Cox Proportional Hazards
  • 55:30 17.
    Summary
  • 57:16 18.
    Clustering Analysis
  • 1:05:24 19.
    Distances Between Clusters Used For Hierarchical Clustering
  • 1:07:44 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
  • 1:10:24 21.
    Hierarchical Clustering1
  • 1:12:17 22.
    Hierarchical Clustering2
  • 1:15:01 23.
    Partitional Algorithms: K-means / K-medians
  • 1:19:48 24.
    Partitional Algorithms: K-means / K-medians
  • 1:21:03 25.
    Partitional Algorithms: Self-Organizing Map Algorithm
  • 1:22:07 26.
    Artificial Neural Network
  • 1:22:39 27.
    The SOM Algorithm - A Summary of Steps1
  • 1:24:13 28.
    The SOM Algorithm - A Summary of Steps2
  • 1:24:55 29.
    The SOM Algorithm - A Summary of Steps3
  • 1:26:41 30.
    The SOM Algorithm - A Summary of Steps5
  • 1:27:43 31.
    Supervised Algorithm
  • 1:29:34 32.
    Support Vector Machine
  • 1:30:26 33.
    K-Nearest Neighbor (K-NN)
  • 1:31:12 34.
    Decision Trees / Random Forest
  • Index
  • Notes
  • Comment
  • Fullscreen
Comparative Gene-Expression Analysis I: Hybridization-based techniques (0316)
Duration: 1:33:29, Browse: 492, Last Updated: 2021-03-16
    • 00:00 1.
      Decide Which Genes are Significantly Regulated ?
    • 03:17 2.
      Decide Which Genes are Significantly Regulated ?
    • 10:14 3.
      Decide Which Genes are Significantly Regulated ?
    • 13:21 4.
      Decide Which Genes are Significantly Regulated ?
    • 16:59 5.
      Statistical Distribution
    • 20:56 6.
      Decide Which Genes are Significantly Regulated ?
    • 26:57 7.
      Question
    • 29:43 8.
      Decide which genes are significantly regulated ?3
    • 35:23 9.
      Permutation test
    • 37:12 10.
      QuestionWhat is F-test? Mann–Whitney tests Kruskal–Wallis tests Analysis of Variance Permutation test
    • 37:50 11.
      Concept of Biostatistics About Nominal (Categorical) Variable
    • 43:20 12.
      Concept of Biostatistics About Nominal Variable
    • 45:47 13.
      Survival Analysis
    • 47:33 14.
      Univariate Method: Kaplan-Meier Survival Curves
    • 52:11 15.
      Web Tool: Kaplan-Meier Plotter
    • 53:20 16.
      Multivariate Method: Cox Proportional Hazards
    • 55:30 17.
      Summary
    • 57:16 18.
      Clustering Analysis
    • 1:05:24 19.
      Distances Between Clusters Used For Hierarchical Clustering
    • 1:07:44 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
    • 1:10:24 21.
      Hierarchical Clustering1
    • 1:12:17 22.
      Hierarchical Clustering2
    • 1:15:01 23.
      Partitional Algorithms: K-means / K-medians
    • 1:19:48 24.
      Partitional Algorithms: K-means / K-medians
    • 1:21:03 25.
      Partitional Algorithms: Self-Organizing Map Algorithm
    • 1:22:07 26.
      Artificial Neural Network
    • 1:22:39 27.
      The SOM Algorithm - A Summary of Steps1
    • 1:24:13 28.
      The SOM Algorithm - A Summary of Steps2
    • 1:24:55 29.
      The SOM Algorithm - A Summary of Steps3
    • 1:26:41 30.
      The SOM Algorithm - A Summary of Steps5
    • 1:27:43 31.
      Supervised Algorithm
    • 1:29:34 32.
      Support Vector Machine
    • 1:30:26 33.
      K-Nearest Neighbor (K-NN)
    • 1:31:12 34.
      Decision Trees / Random Forest
    Location
    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
    Duration
    1:33:29