Inhalte

Part 1: Introduction to Biomedical Data Science Part 2: Programming for Biomedical Data Analysis Part 3: Bioinformatic Analysis of Biomedical Data Part 4: Data Exchange Formats and Markup Languages Part 5: Data Visualization and Communication Part 6: Biomedical Data Integration and Validation Part 7: Special Topics in Biomedical Data Science

Lernziele

The studies aim to provide an interdisciplinary education, combining medicine, computer science, and data analysis skills. Students learn to work with small exemplary real world datasets from biomedical research. The goal is to enable graduates to derive new knowledge, more accurate diagnoses, and improved therapies by connecting different areas of expertise. Upon completing the Bachelor course, students will be able to: • Apply statistical concepts and methods to analyse and interpret biomedical data, including hypothesis testing, regression, and machine learning. • Use bioinformatic tools and databases to analyse and interpret genomic, proteomic, and other types of biomedical data. • Program in R or Python to perform data analysis, visualization, and modelling tasks, including data wrangling, data visualization, and statistical modeling. • Use markup languages (YAML, Markdown, ECMAScript) to document and communicate biomedical data analysis results. • Apply data exchange formats (JSON, XML) to import, export, and manipulate biomedical data. • Use LaTeX to create professional-quality documents and reports for biomedical data analysis results. • Integrate multiple data sources and formats to perform comprehensive biomedical data analysis. • Evaluate the quality and limitations of biomedical data and develop strategies for data validation and quality control. • Communicate complex biomedical data analysis results effectively to diverse audiences, including healthcare professionals, researchers, and policymakers. • Learn about ethical and legal principles to biomedical data analysis, including issues related to data privacy, security, and informed consent. Overall, biomedical data science programs provide a broad foundation in medicine, informatics, and data analysis methods, with opportunities to deepen knowledge.

Prüfungsleistung

Written examination (120 min)

Literatur (1)

"Introduction to Biomedical Data Science" by Robert Hoyt and Robert Muenchen

Bemerkungen

on campus, optional online