Search result: Catalogue data in Autumn Semester 2018
| Core Courses|
Students need to acquire a total of 8 ECTS in lectures in this category.
The list of core courses is a closed list, no other course can be added to this category.
Students need to pass both lectures offered in this category.
Does not take place this semester.
This lecture will take place again in Spring Semester 2019.
|O||4 credits||3G||N. Beerenwinkel, S. Reddy|
|Abstract||This lecture course is an introduction to Systems Genomics. It addresses how fundamental questions in biological systems are studied and how the resulting data is statistically analyzed in order to derive predictive mathematical models. The focus is on viewing biology from a genomic perspective, which requires high-throughput experimental methods (e.g., RNA-seq, genome-scale screening, single-cell|
|Objective||The goal of this course is to learn how a detailed quantitative description of genome biology can be employed for a better understanding of molecular and cellular processes and function. Students will learn fundamental questions driving the field of Systems Genomics. They will also be introduced to traditional and advanced state-of-the-art technologies (e.g., CRISPR-Cas9 screening, droplet-microfluidic sequencing, cellular genetic barcoding) that are used to obtain quantitative data in Systems Genomics. They will learn how to use these data to develop mathematical models and efficient statistical inference algorithms to recognize patterns, molecular interrelationships, and systems behavior. Finally, students will gain a perspective of how Systems Genomics can be used for applied biological sciences (e.g., drug discovery and screening, bio-production, cell line engineering, biomarker discovery, and diagnostics).|
|Content||Lectures in Systems Genomics will alternate between lectures on (i) biological questions, experimental technologies, and applications, and (ii) statistical data analysis and mathematical modeling. Selected complex biological systems and the respective experimental tools for a quantitative analysis will be presented. Some specific examples are the use of RNA-sequencing to do quantitative gene expression profiling, CRISPR-Cas9 genome scale screening to identify genes responsible for drug resistance, single-cell measurements to identify novel cellular phenotypes, and genetic barcoding of cells to dissect development and lineage differentiation. |
-- Next-generation sequencing
-- Biological network analysis
-- Functional and perturbation genomics
-- Single-cell biology and analysis
-- Genomic profiling of the immune system
-- Genomic profiling of cancer
-- Evolutionary genomics
-- Genome-wide association studies
Selected genomics datasets will be analyzed by students in the tutorials using the statistical programming language R and dedicated Bioconductor packages.
|Lecture notes||The PowerPoint presentations of the lectures as well as other course material relevant for an active participation will be made available online.|
|Literature||-- Do K-A, Qin ZS & Vannucci M (2013) Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput Data, Cambridge University Press|
-- Klipp E. et al (2009) Systems Biology, Wiley-Blackwell
-- Alon U (2007) An Introduction to Systems Biology, Chapman & Hall
-- Zvelebil M & Baum JO (2008) Understanding Bioinformatics, Garland Science
|636-0102-00L||Advanced Bioengineering||O||4 credits||3S||S. Panke, Y. Benenson, P. S. Dittrich, M. Fussenegger, A. Hierlemann, M. H. Khammash, D. J. Müller, R. Paro, R. Platt, T. Schroeder|
|Abstract||This course provides an overview of modern concepts of bioengineering across different levels of complexity, from single molecules to systems, microscaled reactors to production environments, and across different fields of applications|
|Objective||Students will be able to recognize major developments in bioengineering across different organisms and levels of complexity and be able to relate it to major technological and conceptual advances in the underlying sciences.|
|Content||Molecular and cellular engineering; Synthetic biology: Engineering strategies in biology; from single molecules to systems; downscaling bioengineering; Bioengineering in chemistry, pharmaceutical sciences, and diagnostics, personalized medicine.|
|Lecture notes||Handouts during class|
|Literature||Will be announced during the course|
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