Methods in Bioanalytics
Methoden in der Bioanalytik
8 LPSoSeEN
Voraussetzungen
Zwingend, im Wortlaut
Only applies to the Master Biotechnology PO 2018 with 4 semesters standard period of study: Successfull completion of module • 12739 - Research Internship
Empfohlen, im Wortlaut
Basic knowledge in Cell biology, Biochemistry, applied biostatistics and bioinformatics.
Inhalte
• Sterile working technique, media preparation • Routine maintenance of cell lines: Medium replacement, subculture of adherent cells • Cryopreservation: Freezing and thawing of cells • Contamination control: Microscopical observation, etc. • Characterization of human (tumor) cells or cell lines • Morphology: microscopy of cells • Proliferation: Growth curve, population doubling-time • Testing of (mouse monoclonal) antibodies ((m)Ab). Immunocytochemistry and immunochemistry with (m)Abs • Comparison of different cell assays e.g. gamma H2AX-Assays and FISH assays • Assesment of the effect of chemoterapeutic substances Contents of the seminar: Deepening the knowledge of the methods used in the labcourse. Methods in applied statistical bioinformatics, literate programming and report generation (Remarkdown or Jupyter notebook).
Lernziele
First the students expand their professional competencies in training the skills in sterile cell culture techniques and practice the performance of special cell assays (incl. analysis of DNA damage upon treatment with single (etoposide) and multiple chemotherapeutic substances, FISH to asses genomic alterations of cancer cells). In particular, the cell assays have relevance in precision medicine and pharmacology/pharmaceutical research. Furthermore, they broaden their methodological background in analysis, interpretation and reporting of lab data by different methods used in applied statistical bioinformatics, forensics, pharmaceutical research and precision medicine. By working in small groups the students train also soft skills like the ability to work and communicate in a team. The special task to present and discuss the experimental results train additional soft skills like the ability to communicate orally to individuals and groups and to tailor the oral communication to the level and experience of the audience. The students use appropriate scientific open source software (incl. R statistical computing language, Python general purpose programming language), graphics, and other tools to clarify complex information. The analysis of the data includes methods used in applied statistical bioinformatics and bioanalytical pharmacology. Moreover, the accompanying seminar will train methodological competencies (e.g. media skills), and soft skills like presenting special facts and data and to communicate in a group.
Prüfungsleistung
• Laboratory Work – design, execution, in–lab discussion, and time management (55 %) • Presentation & Discussion (Journal Club of a Research Paper) - each student selects one current research paper from the field of bioanalytics; 15–minute presentation followed by a 10–minute group discussion (15 %) • Written Tests – 3 separate tests (each 30 min.),(15 %) • General knowledge about Methods in Bioanalytics and related topics • Knowledge of statistical bioinformatics and associated methods • Lab–course–specific content • Presentation of Lab–Course Results – two components (15 %) • Lab report (10 pages) produced from a reproducible document (e.g., Quarto, RMarkdown), due at the end of the course • Oral presentation using that reproducible document: 10 minutes for the presentation followed by a 10–minute group discussion
Literatur (8)
- Freshney, Ian: Culture of Animal Cells: A Manual of Basic Technique and Specialized A pplications; 2010
- Lindl, Toni.; Gstraunthaler G.: Zell- und Gewebekultur. Von den Grundlagen zur Laborbank; Spektrum Akademischer Verlag, 6. Auflage, 2008
- Schmitz, Sabine: Der Experimentator Zellkultur, Spektrum Akademischer Verlag 2011
- Logan, M., Biostatistical Design and Analysis Using R: A Practical Guide. 2010
- Selvin, S., 1998. Modern Applied Biostatistical Methods: Using S-Plus, Monographs in Epidemiology and Biostatistics. Oxford University Press, Oxford, New York.
- Lee, J.K., 2010. Statistical Bioinformatics: For Biomedical and Life Science Researchers. Wiley.
- Sencar, H.T., Memon, N. (Eds.), 2013. Digital Image Forensics. Springer New York, New York, NY. https://doi.org/10.1007/978-1-4614-0757-7
- National Research Council (US) Committee on A Framework for Developing a New Taxonomy of Disease, 2011. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease, The National Academies Collection: Reports funded by National Institutes of Health. National Academies Press (US), Washington (DC).
Bemerkungen
The module takes place as a 6 week block course.
Quelle: Modulbeschreibung der BTU · abgerufen 28.09.2026Original