MIT Deep Learning Genomics - Lecture 6 - Regulatory Genomics (Spring 2020)

MIT 6.874 Lecture 6. Spring 2020
Course website: https://mit6874.github.io/
Lecture slides:
Lecturer: Manolis Kellis

Lecture outline:
1. Biological foundations: Building blocks of Gene Regulation
- Gene regulation: Cell diversity, Epigenomics, Regulators (TFs), Motifs, Disease role
- Probing gene regulation: TFs/histones: ChIP-seq, Accessibility: DNase/ATAC-seq
2. Classical methods for Regulatory Genomics and Motif Discovery
- Enrichment-based motif discovery: Expectation Maximization, Gibbs Sampling
- Experimental: PBMs, SELEX. Comparative genomics: Evolutionary conservation.
3. Regulatory Genomics CNNs (Convolutional Neural Networks): Foundations
- Key idea: pixels == DNA letters. Patches/filters == Motifs. Higher == combinations
- Learning convolutional filters == Motif discovery. Applying them == Motif matches
4. Regulatory Genomics CNNs/RNNs in Practice: Diverse Architectures
- DeepBind: Learn motifs, use in (shallow) fully-connected layer, mutation impact
- DeepSea: Train model directly on mutational impact prediction
- Basset: Multi-task DNase prediction in 164 cell types, reuse/learn motifs
- ChromPuter: Multi-task prediction of different TFs, reuse partner motifs
- DeepLIFT: Model interpretation based on neuron activation properties
- DanQ: Recurrent Neural Network for sequential data analysis

Видео MIT Deep Learning Genomics - Lecture 6 - Regulatory Genomics (Spring 2020) канала Manolis Kellis