Introduction to deep learning for bioinformatics with R

Deep learning based techniques have shown remarkable results in domains such as speech synthesis, natural language processing and image vision. Recently, these methods have been applied to the bioinformatic domain and have been shown, for example, to achieve an unprecedented level of performance for the protein folding task. In this workshop we will explore and train deep neural networks using the R programming language on genomic datasets.

Requirements:
Please note: This Workshop requires a basic knowledge of R.
Google account for Google Colab

Agenda:

• Mon, Oct 11, 10am–4pm.
  Deep learning basics, introduction to R keras and tensorflow and Google Colaboratory
• Tue, Oct 12, 9am–4pm.
  Overview about different neural architectures and their application, visualization of training progress with Tensorboard, model inference and inspection
• Wed, Oct 13, 9am–12pm (open end).
  Usage of deepG, a R library to train neural networks on genomic data
  starting from 1pm (optional): Open session, discuss your own projects/data

Apply here - (application deadline: Friday, Sep 10):

https://forms.gle/3iJV2sec7QgoBCcv9

Questions?

bioinformatics@dzif.de

The unit "Bioinformatics and Machine Learning" is looking forward to seeing you in the workshop!