MIT 6.874 Lecture 6. Spring 2020
Course website: mit6874.github...
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
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