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Systems Genomics
Last Updated: 2026-02-05 16:07:59
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. Main Topics: -- Next-generation sequencing -- Transcriptomics -- 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.
Resources
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
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- end-of-semester examination
- Mode
- written 90 minutes
- Aids
- None
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Systems Genomics
Lecture: Wednesday 11-13.
Tutorial: Wednesday 17-18.
This lecture will take place online only (via Zoom). Link will be send to registered students in due time.
Room reserved in Basel: Misrock (BSA E46)
From HS22 only in the autumn semester offered.
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3 h weekly |
Offered In
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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.)
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Computational Biology and Bioinformatics Master (More informations at: )
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Core Courses (Please note that the list of core courses is a closed list. Other courses cannot be added to the core course category in the study plan. Also the assignments of courses to core subcategories cannot be changed. Students need to pass at least one course in each core subcategory. A total of 40 ECTS needs to be acquired in the core course category.)
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Doctorate Biosystems Science and Engineering (More Information at: )
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Subject Specialisation (The courses on offer below are a selection out of a much larger available number of courses. You may look for other courses too. If you are uncertain about the creditability and assessment of the course unit you wish to take, please consult the D-​BSSE Doctoral Administration. This should be done before registering the course unit.)
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