Pattern Discovery in Bioinformatics

author: Jaak Vilo, University of Tartu

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*Slides*
0:00	Pattern Discovery in Bioinformatics
0:41	Topics
1:27	Pattern Discovery
2:16	Bioinformatics - 1
2:50	Bioinformatics - 2
3:08	DNA Structure
4:09	DNA Determines Function
5:18	A Simple Gene
6:41	Species and Individuals
7:30	Cell Structure
9:24	A Unified Theory of Gene Expresion - 1
10:47	A Unified Theory of Gene Expresion - 2
13:58	Gene Regulation - 1
14:59	Gene Regulation - 2
15:25	Gene Regulation - 3
15:44	Gene Regulation - 4
15:48	Gene Regulation - 3
15:49	Gene Regulation - 4
16:17	Gene Regulation - 5
16:48	Gene Regulation - 6
17:23	MicroRNA - 1
17:41	MicroRNA - 2
18:45	MicroRNA - 3
19:16	MicroRNA - 4
19:37	Alignment of MicroRNA Targets
19:54	Sequence Patterns in BI
19:56	Alignment of MicroRNA Targets
20:00	Sequence Patterns in BI
20:10	Biological Applications
20:28	Gene Regulatory Signal Finding
20:45	How Can We Find TF Binding Sites?
21:02	How to Detect Signals in DNA?
21:38	Position Weight Matrices
24:48	Motif Matching
25:02	Motif Discovery
25:33	Common Biological Role
26:02	Microarrays
26:41	How to Know What´s in the Cells? - 1
27:14	How to Know What´s in the Cells? - 2
27:56	Microarray - The “Measurement Device”
28:36	Microarray - After Hybridisation
29:22	Microarray - 2 Colors Mixed
29:31	TIGR 32k Human Arrays
30:14	Affymetrix Wafer and Chip Format
30:57	From Microarray Images to Gene Expression Data - 1
31:58	From Microarray Images to Gene Expression Data - 2
32:15	From Microarray Images to Gene Expression Data - 1
32:24	From Microarray Images to Gene Expression Data - 2
33:02	From Microarray Images to Gene Expression Data - 3
33:22	From Microarray Images to Gene Expression Data - 4
34:18	Cluster of Co-Expressed Genes - Pattern Discovery in Regulatory Regions
35:13	Binomial or Hypergeometric Distribution Tail
35:42	ChIP-Chip (or Sequencing) - 1
36:22	ChIP-Chip (or Sequencing) - 2
36:49	ChIP-Chip (or Sequencing) - 3
37:11	ChIP-Chip (or Sequencing) - 4
38:14	Clustering and Gene Set Enrichment - 1
39:18	- Questions
44:56	Clustering and Gene Set Enrichment - 3
45:43	Clustering and Gene Set Enrichment - 4
46:48	Clustering and Gene Set Enrichment - 5
47:01	Clustering and Gene Set Enrichment - 6
47:17	Clustering and Gene Set Enrichment - 5
47:19	- Questions
48:11	Clustering and Gene Set Enrichment - 7
48:17	Clustering and Gene Set Enrichment - 8
48:40	Clustering and Gene Set Enrichment - 9
49:03	Find a Common Function (Pattern)
49:06	Clustering and Gene Set Enrichment - 9
49:13	Find a Common Function (Pattern)
51:25	Previously Known Functions - 1
51:51	Previously Known Functions - 2
52:30	Previously Known Functions - 3
52:39	Previously Known Functions - 4
53:26	Previously Known Functions - 5
53:27	Previously Known Functions - 6
53:40	Previously Known Functions - 5
53:41	Previously Known Functions - 6
53:53	Previously Known Functions - 5
54:11	KEGG: Biosynthesis of Steroids Query
54:12	Previously Known Functions - 6
54:22	KEGG: Biosynthesis of Steroids Query
55:15	p-Value
56:19	SCS - Set Counts and Sizes Threshold
59:04	Motif Discovery in Sequences
61:00	Cluster of Co-Expressed Genes - Pattern Discovery in Regulatory Regions - 1
61:08	Cluster of Co-Expressed Genes - Pattern Discovery in Regulatory Regions - 2
61:09	Cluster of Co-Expressed Genes - Pattern Discovery in Regulatory Regions - 1
62:58	Cluster of Co-Expressed Genes - Pattern Discovery in Regulatory Regions - 2
64:24	Cluster of Co-Expressed Genes - Pattern Discovery in Regulatory Regions - 3
64:54	Pattern vs Cluster “Strength”
67:13	Suffix Tree – Represent All Suffixes
67:18	Pattern vs Cluster “Strength”
67:34	Suffix Tree – Represent All Suffixes

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