392160 Graph Neural Networks in Biology (S) (SoSe 2024)
Contents, comment
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The recent surge of machine learning (ML) has opened up various opportunities when analyzing biological datasets. Graph Neural Networks (GNNs) are a fairly new deep learning model capable of handling biological data in the best way overall.
The seminar will start with an introductory lecture. The earliest and most recent approaches will be discussed, together with their use cases and drawbacks. The mini lecture will be followed by two lectures in which it will be presented how to write technical reports and how to prepare a good presentation. Then will seminar presentations, to be presented in small groups of 1-2 students.
The course will be held entirely in English.
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period | |
|---|---|---|---|---|---|
| weekly | Di | 16-18 | X-B2-101 | 08.04.-19.07.2024 |
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-BDS Biomedical Data Science for Modern Healthcare Technology | Ausgewähltes Seminar oder Projekt | Study requirement
|
Student information |
| 39-Inf-WP-CLS-x Computational Life Sciences (Schwerpunkt) | Vertiefendes Seminar | Student information | |
| 39-Inf-WP-DS-x Data Science (Schwerpunkt) | Vertiefendes Seminar | Student information | |
| - | Graded examination | Student information | |
| 39-M-Inf-INT-adv Advanced Interaction Technology | Advanced Interaction Technology: Seminar 1 | Study requirement
|
Student information |
| Advanced Interaction Technology: Seminar 2 | Graded examination
|
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
E-Learning Space
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- SS2024_392160@ekvv.uni-bielefeld.de
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- Coverage:
- 19 Students to be reached directly via email
- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Wednesday, January 10, 2024
- Last update times:
- Friday, February 2, 2024
- Last update rooms:
- Friday, February 2, 2024
- Type(s) / SWS (hours per week per semester)
- S / 2
- Department
- Faculty of Technology
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