Workload:
90 h
|
Module Number INF3658 |
Module Title Machine Learning in Bioinformatics (Proseminar) |
Type of Module Elective Compulsory |
|---|---|---|
| ECTS | 3 | |
|
Work load - Contact time - Self study |
Workload:
90 h Class time:
30 h / 2 SWS Self study:
60 h |
|
| Duration | 1 Semester | |
| Frequency | In the winter semester | |
| Language of instruction | German | |
| Type of Exam | Presentation and essay |
|
| Lecture type(s) | Proseminar | |
| Content | Machine learning plays an important role in bioinformatics and chemoinformatics for data analysis and modeling. Basic machine learning methods, their theoretical foundations, and their practical applications in bioinformatics (e.g., in sequence analysis, protein similarity analysis, drug design, protein-ligand interactions, transcription factor binding site prediction, etc.) are presented. In addition, validation strategies and parameter optimization methods are presented. |
|
| Objectives | Machine learning in bioinformatics: In addition to the subject-specific skills of the proseminar, students also learn how to scientifically analyse a topic, prepare a scientific presentation, give a presentation, communicate with an audience, engage in critical scientific discourse and write a scientific paper on their seminar topic. |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%) |
|
| Prerequisite for participation | There are no specific prerequisites. | |
| Lecturer / Other | ||
| Literature | - |
|
| Last offered | unknown | |
| Planned for | currently not planned | |
| Assigned Study Areas | BIOINFM1510, INFM1510, MDZINFM1510, MEINFM1510 | |