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