Module Number BIOINF3360 |
Module Title Computational Immunomics |
Type of Module Elective Compulsory |
---|---|---|
ECTS | 6 | |
Work load - Contact time - Self study |
Workload:
180 h Class time:
60 h / 4 SWS Self study:
120 h |
|
Duration | 1 Semester | |
Frequency | Irregular | |
Language of instruction | German | |
Type of Exam | Exam, exercise performance can flow into the exam as bonus points |
|
Lecture type(s) | Lecture, Tutorial | |
Content | This lecture provides an introduction to the world of immunoinformatics. It deals with the application of informatics methods to solve immunological problems, such as the development of new vaccines. Core topics include introduction to immunology, machine learning methods, MHC-peptide binding prediction, antigen processing prediction, vaccine design, and systems immunology. |
|
Objectives | Understanding in dealing with immunological data. Transfer of methodological competences (machine learning) to concrete biological applications (immunology). Ability to develop and use own tools for immunoinformatics in a team. Project work strengthens teamwork and presentation skills. |
|
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 | Kohlbacher | |
Literature | Vorlesungsfolien werden in der Vorlesung verteilt. Goldsby, Kindt, Osborne, Kuby: Immunology (5th ed.), Freeman, 2003; Murphy \& Weaver: |
|
Last offered | Sommersemester 2020 | |
Planned for | Sommersemester 2024 | |
Assigned Study Areas | BIOINFM2210, BIOINFM2510, INFM2510, MDZINFM2510, MDZINFM3110, MEINFM3210 |