Michael Ristow: Catalogue data in Autumn Semester 2021 |
| Name | Dr. Michael Ristow |
| Field | Energy Metabolism |
| Address | Charité - CCM - CC13 - IEED Hessische Str. 3-4 Inst. f. Exp. Endo/Diabetologie 10115 Berlin GERMANY |
| Department | Health Sciences and Technology |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 376-0303-00L | Colloquium in Translational Science (Autumn Semester) | 1 credit | 1K | M. Ristow, A. Alimonti, N. Cesarovic, C. Ewald, V. Falk, J. Goldhahn, K. Maniura, R. M. Rossi, S. Schürle-Finke, G. Shivashankar, E. Vayena, V. Vogel | |
| Abstract | Current topics in translational medicine presented by speakers from academia and industry. | ||||
| Learning objective | Getting insight into actual areas and problems of translational medicine. | ||||
| Content | Timely and concise presentations of postgraduate students, post-docs, senior scientists, professors, as well as external guests from both academics and industry will present topics of their interest related to translational medicine. | ||||
| Prerequisites / Notice | No compulsory prerequisites, but student should have basic knowledge about biomedical research. | ||||
| 376-1723-00L | Big Data Analysis in Biomedical Research  | 4 credits | 2V + 2U | E. Araldi, M. Ristow | |
| Abstract | Biomedical datasets are increasing in size and complexity, and discoveries arising from their analysis have important implications in human health and biotechnological advances. While the potential of biomedical dataset analysis is considerable, preclinical researchers often lack the computational tools to analyze them. This course will provide the basis of data analysis of large biomedical data | ||||
| Learning objective | This course aims to provide practical tools to analyze large biomedical datasets, and it is tailored towards experimental researchers in the life sciences with minimal prior programming experience, but with a strong interest in exploring big data to solve own research problems. Through theoretical classes, practical demonstrations, in class exercises and homework, the participants will master computational methods to independently manipulate large datasets, effectively visualize big data, and analyze it with appropriate statistical tools and machine learning approaches. For the final assessment, students will conduct an independent data analysis project based on a biomedical problem of their choosing and using publicly available population-based biomedical datasets. | ||||
| Content | While learning the programming skills needed to manipulate and visualize the data, participants will learn the statistical and modeling approaches for big data analysis. The course will cover: •Basis of Python programming and UNIX; •High performance computing; •Manipulation and cleaning of large datasets with Pandas; •Visualization tools (Matplotlib, Seaborn); •Machine learning and numerical libraries (SciPy, NumPy, Statsmodels, Scikit-Learn). •Statistical analysis and modeling of big data, and applications to biomedical datasets (statistical learning, distributions, linear and logistic regressions, principal component analysis, clustering, classification, time series analysis, tree-based methods, predictive models). | ||||
| Prerequisites / Notice | Basic understanding of mathematics and statistics, as taught in basic courses at the Bachelor`s level. | ||||
| 377-0503-01L | Geriatrics Only for Human Medicine BSc | 1 credit | 1V | M. Ristow, J. Goldhahn, R. W. Kressig, M. Martin, further lecturers | |
| Abstract | Fundamentals and relevance of the aging process, as well as its biochemical, physiological and evolutionary basis. Insights into its individual as well as economic impact, including interventional and pharmacological treatment options. | ||||
| Learning objective | Upon successful completion of the module, students should be able to 1. correctly describe the biological bases of the aging process; 2. derive physical and pharmacological choices to modulate the aging process; 3. understand the social and psychological implication of aging; 4. describe the specificities of geriatric medicine in the stationary setting; 5. identify the age-specific differences in both diagnostics and therapeutics. | ||||
| Content | Fundamentals and relevance of the aging process, as well as its biochemical, physiological and evolutionary basis. Insights into its individual as well as economic impact, including interventional and pharmacological treatment options. | ||||
| Prerequisites / Notice | Prerequisites: LE 377-0105-00L Bewegungsapparat LE 377-0107-00L Nervensystem LE 377-0201-00L Herz-Kreislauf-System LE 377-0203-00L Atmungs-System LE 377-0205-00L Nieren und Homöostase LE 377-0301-01L Blut, Immunsystem LE 377-0301-02L Ernährung und Verdauung LE 377-0301-03L Endokrinologie, Stoffwechsel LE 377-0401-00L Sinnesorgane LE 377-0403-00L Haut und Anhangsorgane | ||||
| 752-6306-AAL | Physiology and Anatomy II Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement. Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit. | 3 credits | 6R | D. Burdakov, M. Ristow | |
| Abstract | Imparts a basic understanding of physiology and anatomy in man, focusing on the close interrelations between morphology and function of the human organism. This is fostered by discussing all subjects from a functional point of view. A major topic of the lecture is food intake and digestion with its correlated endocrine and metabolic processes. | ||||
| Learning objective | After this course the students are able to understand basic principles of systems physiology and the mechanisms of the function of the major organ systems. | ||||