Lecture: Introduction to Biomedical Systems Modeling and Data Science - Details

Lecture: Introduction to Biomedical Systems Modeling and Data Science - Details

You are not logged into Stud.IP.

General information

Course name Lecture: Introduction to Biomedical Systems Modeling and Data Science
Course number INF-0516
Semester WS 2024/25
Current number of participants 11
Home institute Lehrstuhl für Modellierung und Simulation biologischer Prozesse - Prof. Dr. Andreas Raue
Courses type Lecture in category Teaching
First date Wednesday, 23.10.2024 08:15 - 09:45, Room: (Seminarraum 1055-N)
Pre-requisites For the computer practice, the plan is to mainly use Python and Jupyter Notebooks. Knowledge of standard packages (such as numpy, scipy, scikit-learn, pandas, matplotlib, etc.) and the creation of virtual environments (conda) would be ideal but can also be developed during the course. In principle, participants can also use other programming languages to complete the tasks (e.g., R), but no “hands-on” support can be provided for those.
Veranstaltung findet in Präsenz statt / hat Präsenz-Bestandteile Yes
Hauptunterrichtssprache englisch
Weitere Unterrichtssprache(n) deutsch
Literaturhinweise For further reading, not a blueprint for this lecture!

- "Introduction to Machine Learning" by Ethem Alpaydin
- "Machine Learning" by Tom M. Mitchell
- "Introduction to System Biology" by Edda Klipp
- "A First Course in Systems Biology" by Eberhard O. Voit
ECTS points 5

Rooms and times

(Seminarraum 1055-N)
Wednesday: 08:15 - 09:45, weekly (13x)

Module assignments

Comment/Description

Part 1: Data Science
- Introduction Biomedical Data Science, Omics, statistics and data visualizations
- Differential (gene expression) analysis, statistical testing, correlation
- Clustering, heatmaps, dendrograms, linear models
- Gene set enrichment analysis, nonlinear models, neural network models

Part 2: Systems Modeling
- Introduction to mechanistic models and dynamical systems
- Formalism for ordinary differential equation models
- Numerical solvers and modeling biochemical reactions
- Cellular signaling models and model parameterization