6.047/6.878/HST.507 Fall 2020 Prof. Manolis Kellis
Computational Biology: Genomes, Networks, Evolution, Health
Machine Learning in Genomics: Dissecting the circuitry of Human Disease
Latest slides and course today: http://compbio.mit.edu/6047
Fall 2020 slides and materials: http://stellar.mit.edu/S/course/6/fa20/6.047/materials.html
OVERVIEW
0:00 Lecture 10 overview
0:43 Regulatory motif biology and importance
8:23 Motif information and PWMs
14:20 Diversity of motifs across domains
15:20 Approaches for motif discovery
19:20 Challenges in regulatory genomics
23:10 Enrichment-based discovery methods
27:07 Expectation maximization
31:01 Motif M and Background B representation
33:20 Starting position probabilities Zij
37:37 E step estimating Zij from motif
41:11 M step Greedy vs Gibbs Sampling vs EM
44:18 M step estimating motif from Zij
46:44 Gibbs Sampling
52:24 Evolutionary signatures for de novo motif discovery
55:40 Three genome-wide conservation scores
1:00:36 Enumeration approach for TF motif discovery
1:01:26 Interpreting discovered motifs
1:05:36 Evolutionary signatures for instance identification
1:08:00 Branch Length Score Computation
1:10:57 From Branch Length to Confidence Score
1:15:34 TF in promoters vs MicroRNA motifs in 3UTRs
1:17:34 Validating discovered motif instances
1:19:31 Regulatory Networks from TFs to Target Genes
1:20:05 Lecture summary
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