6.874/6.802/20.390/20.490/HST.506 Spring 2021 Prof. Manolis Kellis
Deep Learning in the Life Sciences / Computational Systems Biology
Playlist:    • MIT Deep Learning in Life Sciences - ...  
Latest slides and course today: http://compbio.mit.edu/6874
Spring 2021 slides and materials: http://mit6874.github.io/

0:00 Introduction
1:25 Obtaining gene expression data
6:05 Analyzing gene expression data
12:16 Up-sampling
13:20 Compressive sensing
16:30 Predicting splicing
17:40 Enchancer discovery
19:05 STARR-seq
22:00 Enchancer detection with weakly supervised learning
26:45 Model performance
31:15 Deep learning in gene expression analysis
43:18 Connectivity map project
48:02 Predicting gene expression from landmark genes
50:40 Deep generative models for genomics
52:07 Autoencoders
53:40 Generative models and variational autoencoders
1:02:14 Conditional VAE
1:05:20 Predicting splicing from primary sequence
1:08:20 RNA splicing
1:09:21 Decoding splicing with deep learning
1:10:51 Model performance, interpretation, and application