Deep Learning in Life Sciences

As part of the Seed4EU+ action within the 4EU+ alliance of European universities, Heidelberg University will coordinate a joint course on Applications of Deep Learning in Life Sciences (DeepLife) involving the universities of Paris-Sorbonne, Warsaw, Prague, Milano and Heidelberg. The purpose of this course is to give an insight in the very active field of DL in the field of biomedicine and highlight recent examples of applications in three distinct areas:

1. single-cell genomics
2. protein bioinformatics
3. biomedical image analysis.

Important links:

• GitHub repo with course material
• Discussion forum
• Private repo for supervisors

Organization

This course will be organized in 4 blocks over 14 weeks (start: week of 26.02.2024)

1. Basic concepts in deep learning – 4 weeks
2. DL in single-cell genomics – 3 weeks
3. DL in protein bioinformatics - 4 weeks
4. DL in image analysis – 3 weeks
   

Check the program for details.

The course format will comprise a weekly 90-minute online lecture and a weekly hybrid (in-person/online) practical Python session.

Lectures will be given online by teachers from all participating universities. Lectures and practical exercises on all three application areas will be centered around one recent publication illustrating a specific application and method.

The course will end with a 2-day workshop and hackathon meeting in Heidelberg on 14-16 June 2024 during which students will be able to implement a short project and listen to scientific lectures.

Intended audience and evaluation

DeepLife is designed for master’s students from the participating universities, as well as those enrolled in graduate schools. Evaluation will be based on a final online exam and the assessment of practical exercise assignments. Ahead of the course, participants are expected to fresh-up their knowledge on basic notions. Check the list of prerequisites with corresponding teaching resources to cover fundamental concepts. Successful participants will earn 4 ECTS credits (might depend on your university, check with your local coordinator!).

Contact person for information

Prof. Dr. Carl Herrmann – IPMB carl.herrmann@uni-heidelberg.de

Registration: Contact your local coordinator; Registration for Heidelberg students: s.wetzel@uni-heidelberg.de