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Understanding circadian clock function in human cancers using data science

Bharath Ananthasubramaniam, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, Biologie 


Near 24h physiological rhythms, called circadian rhythms, are essential to human health and are altered in many pathologies including cancer. Due to the difficulty of repeatedly sampling human tissues, little is known about in-vivo rhythms in human tissues or in tumors.  In this X-Research Group, students will learn to apply a state-of-the-art machine learning algorithm to public transcriptomic data to get an unprecedented first look at clock function in their chosen tumors. Lectures will provide the necessary biological and computational foundations. Students will learn to curate data, test hypotheses, visualize results and contrast insights against the literature on this open research problem. This course targets advanced Bachelor/Master students with at least a strong interest in biology and basic programming knowledge in R/Python. The course will consist of lectures followed by project work (as a block course). Exact schedule will be decided with students at the course start.

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