551-0338-00L Current Approaches in Single Cell Analysis (University of Zurich)
| Semester | Spring Semester 2021 |
| Lecturers | B. Bodenmiller, University lecturers |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Comment | No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: BME327 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html |
Courses
| Number | Title | Hours | Lecturers | ||||
|---|---|---|---|---|---|---|---|
| 551-0338-00 V | Current Approaches in Single Cell Analysis (University of Zurich) **together with University of Zurich** | 2 hrs |
| B. Bodenmiller, University lecturers |
Catalogue data
| Abstract | In this lecture, we will discuss the most important single cell approaches, the questions they can address and current developments. We will cover single cell: genomics, transcriptomics, proteomics (CyTOF mass cytometry), metabolomics and highly multiplexed imaging. Finally, we will also discuss the latest approaches for the analysis of such generated highly multiplexed single cell data. |
| Learning objective | On completion of this module the students should be able to: - explain the basic principles of single cell analysis techniques - identify and justify the limitations of the current single cell technologies and suggest reasonable improvements - know the basic challenges in data analysis imposed by the complex multi parameter data. Key skills: On completion of this module the students should be able to: - summarize and discuss the impact these technologies have on biology and medicine - design biological and biomedical experiments for which single cell analysis is essential |
| Content | Currently single cell analysis approaches revolutionize the way we study and understand biological systems. In all biological and biomedical settings, cell populations and tissues are highly heterogeneous; this heterogeneity plays a critical role in basic biological processes such as cell cycle, development and organismic function, but is also a major player in disease, e.g. for cancer development, diagnosis and treatment. Currently, single cell analysis techniques are rapidly developing and find broad application, as the single cell measurements not only enable to study cell specific functions, but often reveal unexpected biological mechanisms in so far (assumed) well understood biological processes. In this lecture, we will discuss the most important single cell approaches, the questions they can address and current developments. We will cover single cell genomics, single cell transcriptomics, single cell proteomics (CyTOF mass cytometry), single cell metabolomics and highly multiplexed single cell imaging. Finally, we will also discuss the latest approaches for the analysis of such generated highly multiplexed single cell data. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 2 credits |
| Examiners | B. Bodenmiller |
| Type | graded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
| Additional information on mode of examination | Registration modalities, date and venue of this performance assessment are specified solely by the UZH. |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |
