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551-0500-00L 6 Credits BSC D-CHAB , D-BIOL
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Application of Deep Learning Models in Biology

Lecturers & Examiners: Prof. Dr. Pedro Beltrao
Number of participants limited to 15. The enrolment is done by the D-BIOL study administration.
VVZ CR n/a

Last Updated: 2026-06-01 11:33:00

Abstract

Modern biology research generates very large datasets and analysing these to extract meaningful relationships is now a major bottleneck which is aided by machine learning methods. Neural network models in particular are able to learn rules from such datasets to make predictions about biological systems This course will provide a practical introduction to neural network models in biology.

Objective

In this course the students will learn how to apply deep learning methods for the analysis of biological data (e.g. images, DNA sequences, protein sequences). The course will provide a basic foundation on neural networks but focus primarily on practical use of neural network models for practical application to problems in biology.

Resources

Lecture Notes

Lecture Notes, Literature

General Information

Language
English
Levels
BSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Grading criteria:60% for the project; 20% for each of 2 quizzes.Students are obliged to be present throughout the block course.Cancellation: If you have to deregister from a course that has been assigned to you (just emergency reasons), please notify in written the course coordinator at least four weeks before the course starts, for courses in the 1st quarter, a cancellation period of one week applies. The study secretariat D-BIOL must also be informed (email CC [email protected]) so that the enrollment is deleted. Otherwise the course is considered as "failed".

Course Components

Type Title Time & Place Hours
practical/laboratory course Application of Deep Learning Models in Biology
Permission from lecturers required for all students. Block course in the 1st quarter of the spring semester
  • Tue 12:45-16:30 (HPV F 7.1)
  • Wed 07:45-16:30 (HPV F 7.1)
  • Thu 07:45-16:30 (HPV F 7.1)
  • Fri 07:45-16:30 (HPV F 7.1)
100 h semesterly

Offered In