Aim of the Course
The goal of the course is to allow Bachelor and Master students to engage in a current research project (here circadian rhythms in different human tumors). I will guide each of you through your chosen cancer dataset to answer the central question “are there circadian rhythms in in-vivo human tumors?". We will work as a group, first learning some background, and then performing this analysis collaboratively, while not knowing what we will learn from each analysis (i.e., doing research).
Near 24h biological rhythms, called circadian rhythms, are essential to human health and their disruption is associated with several diseases. Measuring rhythms in a human under health and disease requires measurements at regular time intervals over one or more cycles known as a timeseries. But there are practical and ethical barriers to repeatedly sampling most internal human tissues.
To quantify rhythms in internal tissues, we developed a new machine learning algorithm (called COFE) for de novo profiling of clock-regulated entities in human tissues from population biosamples. In this Research Group, students will apply COFE to transcriptomic data from their chosen cancer tissue from the public The Cancer Genome Atlas to get an unprecedented first look at clock function in different tumors. Students will learn to process data, statistically test hypotheses and contrast insights against the literature. They will thus get a practical introduction to computational biology and data science.
Time & Location
- Winter Semester (WiSe) 2023/2024 (19 October, 2023 - 11 February, 2024)
- Organizational meeting: 10 October, 2023 - Hybrid (online/presence)
- Online programming course: 17 October, 2023 – 21 November, 2023
- Tentative lectures times: Tuesdays 10:00-12:00, from 28 November, 2023 (Times to be agreed upon at first meeting)
- Block course End of January or February, 2024 (Decided at first meeting)
- Meeting location: Institute for Theoretical Biology, SR302, Phillipstr. 13, Haus 20 (Campus Nord), 10115 Berlin-Mitte
The course will consist of the following:
- Online/in-person lectures on circadian rhythms, cancer and high-throughput data analysis.
- Online course to improve programming for data science in R or Python.
- One-week block course to apply COFE to chosen tumor data and perform follow-up analyses.
- Short report (max. 5 pages) outlining the analysis performed and results obtained.
- Students interested in this seminar need to be have some basic biology background (or at least strong interest)
- Ability of do basic programming in R or Python is mandatory (there will be only time to advance your skills).
- Prior interest or knowledge in cancer or human physiology is valuable but not required.
- This course is suitable for advanced Bachelor and Master students
- This course is open to students of Humboldt-Universität, Freie Universität, Technische Universität and Charité Universitätsmedizin (please register for this course at your respective universities).