6.802/6.874/20.390[J]/20.490/HST.506[J] Spring 2017
Computational Systems Biology: Deep Learning in the Life Sciences


Course Information

Instructor: David Gifford
Classes: TR 1-2:30 (32-141)

Presents innovative approaches to computational problems in the life sciences focusing on deep learning based approaches with comparisons to conventional methods. Topics include protein-DNA interaction, chromatin accessibility, regulatory variant interpretation, medical image understanding, medical record understanding, therapeutic design, and experiment design (the choice and interpretation of interventions). Lecture presentations will be given by faculty and topic specific student groups. Multidisciplinary team-oriented final research project, and teams will complete their project using TensorFlow or other framework. Provides a comprehensive introduction to each life sciences problems, but relies upon students understanding probabilistic problem formulations.

Resources and Links

Recommended Reading: Deep Learning (Adaptive Computation and Machine Learning series)
TensorFlow Tutorials
TensorFlow Applied to Standard Data Sets
An Introduction to Deep Learning Approaches in Computational Biology

Course Schedule

Lecture Date Topic Deadlines
1 February 7 Machine Learning in the Computational Life Sciences
2 February 9 Introduction to TensorFlow
3 February 14 Dimensionality Reduction
4 February 16 Autoencoders
February 21 No Class - President's Day
5 February 23 Protein-DNA Interactions
6 February 28 Deep Learning for Protein-DNA Interactions
7 March 2 Predicting Chromatin Data
8 March 7 Deep Learning for Predicting Chromatin Data
9 March 9 eQTL Prediction and Variant Prioritization
10 March 14 Deep Learning for eQTL Prediction and Variant Prioritization
11 March 16 Medical Image Understanding
12 March 21 Medical Record Understanding
13 March 23 Experimental Design - Bayesian Networks
March 28 No Class - Spring Vacation
March 30 No Class - Spring Vacation
14 April 4 Bayesian Optimization
15 April 6 Project Proposals Project Proposals due
16 April 11 Project Proposals
17 April 13 Guest Lectures and/or Meetings with Mentors
April 18 No Class - Patriot's Day
18 April 20 Guest Lectures and/or Meetings with Mentors
19 April 25 Guest Lectures and/or Meetings with Mentors
20 April 27 Guest Lectures and/or Meetings with Mentors
21 May 2 Guest Lectures and/or Meetings with Mentors
22 May 4 Guest Lectures and/or Meetings with Mentors
23 May 9 Guest Lectures and/or Meetings with Mentors
24 May 11 Guest Lectures and/or Meetings with Mentors
25 May 16 Final Project Presentations Final Projects due
26 May 18 Final Project Presentations Last Day of Class!