Module Number BIOINF4384 (entspricht BIO-4384) |
Module Title Machine Learning of Single-Cell Dynamics |
Lecture Type(s) Lecture, Tutorial |
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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 | In the summer semester | |
Language of instruction | English | |
Type of Exam | Excercises (not graded) must be passed. Written / oral exam (graded). |
|
Content | Single-cell technologies have been used to reconstruct the dynamics of biological processes, such as signaling, differentiation and development. This course will review different types of technologies that have been developed and used to this end. At the core, this lecture will introduce and discuss different mathematical models for cellular dynamics, as well as classical and machine learning based system identification and model selection approaches to learn such models from single-cell data. |
|
Objectives | (1) Overview of time resolved single-cell technologies |
|
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 | Claassen | |
Literature | Requirements: Programming skills in Python. |
|
Last offered | unknown | |
Planned for | Sommersemester 2024 | |
Assigned Study Areas | BIO-BIO, ML-CS, ML-DIV |