Bernd Bodenmiller: Katalogdaten im Frühjahrssemester 2021

NameHerr Prof. Dr. Bernd Bodenmiller
LehrgebietQuantitative Biomedizin
Adresse
Quantitative Biomedizin
ETH Zürich, HPL H 22
Otto-Stern-Weg 7
8093 Zürich
SWITZERLAND
Telefon+41 44 633 93 93
E-Mailbernd.bodenmiller@biol.ethz.ch
URLhttp://www.bodenmillerlab.com
DepartementBiologie
BeziehungAusserordentlicher Professor

NummerTitelECTSUmfangDozierende
551-0338-00LCurrent Approaches in Single Cell Analysis (University of Zurich)
Der Kurs muss direkt an der UZH belegt werden.
UZH Modulkürzel: BME327

Beachten Sie die Einschreibungstermine an der UZH: Link
2 KP2VB. Bodenmiller, Uni-Dozierende
KurzbeschreibungIn 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.
LernzielOn 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
InhaltCurrently 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.
551-0364-00LFunctional Genomics
Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module BIO 254 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link
3 KP2VC. von Mering, C. Beyer, B. Bodenmiller, M. Gstaiger, H. Rehrauer, R. Schlapbach, K. Shimizu, N. Zamboni, weitere Dozierende
KurzbeschreibungFunctional genomics is key to understanding the dynamic aspects of genome function and regulation. Functional genomics approaches use the wealth of data produced by large-scale DNA sequencing, gene expression profiling, proteomics and metabolomics. Today functional genomics is becoming increasingly important for the generation and interpretation of quantitative biological data.
LernzielFunctional genomics is key to understanding the dynamic aspects of genome function and regulation. Functional genomics approaches use the wealth of data produced by large-scale DNA sequencing, gene expression profiling, proteomics and metabolomics. Today functional genomics is becoming increasingly important for the generation and interpretation of quantitative biological data. Such data provide the basis for systems biology efforts to elucidate the structure, dynamics and regulation of cellular networks.
InhaltThe curriculum of the Functional Genomics course emphasizes an in depth understanding of new technology platforms for modern genomics and advanced genetics, including the application of functional genomics approaches such as advanced sequencing, proteomics, metabolomics, clustering and classification. Students will learn quality controls and standards (benchmarking) that apply to the generation of quantitative data and will be able to analyze and interpret these data. The training obtained in the Functional Genomics course will be immediately applicable to experimental research and design of systems biology projects.
Voraussetzungen / BesonderesThe Functional Genomics course will be taught in English.