Elective Course
Medical Bioinformatics
Course Content Overview
The purpose of the course is to introduce bioinformatics concepts and their application to biomedical data. The following topics are covered in the course:
o Introduction & Biological and medical databases
o Sequence Alignment & BLAST
o Protein Structure and Prediction
o Functional Annotation & Omics Integration
o RNA-Seq and Deep Sequencing Techniques
o Post-hoc RNA-Seq Data Analysis with R
o Machine Learning Applications in Bioinformatics
Course Logistics
o Time & Place for lecture and tutorial: The course will take place every Thursday at 8:30 am in the institute’s PC pool, rooms 1.01, Walter-Rathenau-Str. 11.
o Attendance: To successfully complete the course, students must attend at least 75% of the sessions (maximum of 3 absences allowed).
o Communication: A DISCORD channel is available for course communication, questions, and discussions.
DISCORD channel for the course: [link]
o Final Exam
📅 Date: Thursday, 17.07.2025
🕣 Time: 8:30 a.m.
🏢 Location: Institute’s PC Pool (Rooms 1.01)
📎 Reminder: Please bring your student ID and a valid ID card.
o Exam Review: Exam results can be reviewed during the opening hours of the Institute’s Secretariat in the C_FunGene building.
Course Materials
All slides, exercise sheets, and additional learning materials will be made available on this website in parallel with the weekly sessions.
Lecture
- Lecture – (10.04.2025) – Biological/medical databases [pdf]
- Lecture – (24.04.2025) – BLAST/ sequence alignment
- Lecture – (15.05.2025) – Protein structure /prediction
- Lecture – (5.06.2025) – Functional annotation
- Lecture – (19.06.2025) – RNA-Seq/Deep sequencing
- Lecture – (26.06.2025) – Post-hoc analysis of RNA-Seq data
- Lecture – (10.07.2025) -RNA-seq data analysis using machine learning
Exercise
- Exercise– (17.04.2025)-Database (pdf)
- Exercise- (08.05.2025)-BLAST and sequence alignment
- Exercise- (22.05.2025)-Protein structure prediction
- Exercise- (12.06.2025)-Functional annotation
- Exercise- (03.07.2025)-Differential expression analysis