Manolis Kellis
@manoliskellis1·24.9K subscribers·255 videos
MIT CompBio Lecture 10 - Regulatory Genomics (Fall '19)
Posted
October 8, 2019
Views
1,573
Likes
17
Engagement
1.08%
October 8, 2019
1,573
17
1.08%
Every word spoken in this episode is indexed. Type any phrase to jump straight to the moment it was said.
Type any word or phrase that may have been spoken. Click a result to seek the player to that exact moment.
Try a name, a topic, or a quoted line
See what was published immediately before and after this episode.
1:18:33Now PlayingMIT Computational Biology: Genomes, Networks, Evolution, Health
Prof. Manolis Kellis
Full playlist with all videos in order is here
All slides from Fall 2019 are here
Outline for this lecture:
1. Introduction to regulatory motifs / gene regulation
- Expts vs. comp. Co-regulated genes (EM, Gibbs). Conserv.
2. Expectation maximization: Motif matrix-to-positions
- E step: Estimate motif positions Zij from motif matrix
- M step: Find max-likelihood motif from all positions Zij
3. Gibbs Sampling: Sample from joint (M,Zij) distribution
- Sampling motif positions based on the Z vector
- More likely to find global maximum, easy to implement
4. Evolutionary signatures for de novo motif discovery
- Genome-wide conservation scores, motif extension
- Validation of discovered motifs: functional datasets
5. Evolutionary signatures for instance identification
- Phylogenies, Branch length score -to- Confidence score
Sentinel Indexing in Progress
Metadata and chapters are available. Claim extraction for this episode is pending.
All video content is delivered via YouTube embedded players in accordance with the YouTube Terms of Service. Sentinel provides research tools that promote discovery and accountability across political media.
