MIT CompBio Lecture 09 - Epigenomics II (Fall '19)

MIT 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:

Epigenomics (continued from lecture 8):

5. Learning chromatin states jointly across cell types

- stacking vs. concatenation vs. independent learning

6. Epigenome imputation

===========

3D genome:

1. Methods for studying nuclear genome organization

- Measuring locus-landmark interactions: ChIP, DamID

- Measuring locus-locus interactions: 3C, 4C, 5C, Hi-C, ChIA-PET

2. Processing and normalization of Hi-C datasets

- Correcting for biases and issues with Hi-C data

- Normalization, sources of bias and bias correction

3. Interpretation of data and functional characterization

- Lamina Associated Domains (LADs)

- Topologically Associated Domains (TADs) and other compartments

4. Conservation of nuclear genome organization

- Across species, across cell types

- Sequence basis for conservation?

5. Towards a mechanistic understanding

- Nuclear genome organization through the (single) cell cycle

- (Limitations of) 3D modeling of nuclear genome organization

- Loop extrusion as a potential mechanism for nuclear organization