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Deep Learning for Healthcare Genomics

This workshop teaches you how to apply deep learning to detect chromosome co-deletion and search for motifs in genomic sequences. You’ll learn how to:

  • Understand the basics of convolutional neural networks (CNNs) and how they work
  • Apply CNNs to MRI scans of low-grade gliomas (LGGs) to determine 1p/19q chromosome co-deletion status
  • Use the DragoNN toolkit to simulate genomic data and to search for motifs

Upon completion, you’ll be able to: understand how CNNs work, evaluate MRI images using CNNs, and use real regulatory genomic data to research new motifs.

Prerequisites

Basic familiarity with deep neural networks, basic coding experience in Python or a similar language

Frameworks

TensorFlow, Caffe, DIGITS, Theano, DragoNN

Assessment Type

Multiple choice

NVIDIA Deep Learning AI Resources

https://www.nvidia.com/en-us/deep-learning-ai/education/

What To Bring

Students will just need their own PC with an outside internet connection to access the course materials and labs, they won’t need to install special software – all of that is preloaded on the VMs.

Schedule

Time Topic Instructor
August 9th 2019 Room NB2.100A
9:00 a.m. - 5:00 p.m. TBD