1. Deep Learning for Computational Biology
Tutor, Thrasyvoulos Karydis, MIT Media Lab
The field of computational biology has seen dramatic growth over the past few years, principally due to the advent of high-throughput experimental technologies producing Petabytes of data across different biological scales. As part of this transition, the traditional, systems-based and theory-based, approaches to understand and engineer biology have given place to high-capacity, data-driven deep-learning methods. The goal of this session is to stimulate discussion on how to build, train and interpret data-driven models for biological data, in light of the current experimental work in the field. This session comprises two parts: a talk to present current research problems in computational biology on which deep learning has had a significant impact, with a focus on the presenter’s work on protein biology and a technical tutorial to provide hands-on experience with the standard tools in deep learning and their applications to molecular biology datasets.