Nicola Zamboni: Catalogue data in Autumn Semester 2023

Award: The Golden Owl
Name Prof. Dr. Nicola Zamboni
Inst. f. Molekulare Systembiologie
ETH Zürich, HPM H 45
Otto-Stern-Weg 3
8093 Zürich
Telephone+41 44 633 31 41
RelationshipAdjunct Professor

551-1153-00LSystems Biology of Metabolism
Number of participants limited to 15.
4 credits2VU. Sauer, N. Zamboni
AbstractStarting from contemporary biological problems related to metabolism, the course focuses on systems biological approaches to address them. In a problem-oriented, this-is-how-it-is-done manner, we thereby teach modern methods and concepts.
ObjectiveDevelop a deeper understanding of how relevant biological problems can be solved, thereby providing advanced insights to key experimental and computational methods in systems biology.
ContentThe course will be given as a mixture of lectures, studies of original research and guided discussions that focus on current research topics. For each particular problem studied, we will work out how the various methods work and what their capabilities/limits are. The problem areas range from microbial metabolism to cancer cell metabolism and from metabolic networks to regulation networks in populations and single cells. Key methods to be covered are various modeling approaches, metabolic flux analyses, metabolomics and other omics.
Lecture notesScript and original publications will be supplied during the course.
Prerequisites / NoticeThe course extends many of the generally introduced concepts and methods of the Concept Course in Systems Biology. It requires a good knowledge of biochemistry and basics of mathematics and chemistry.
551-1299-00LBioinformatics Restricted registration - show details 6 credits4GS. Sunagawa, P. Beltrao, V. Boeva, A. Kahles, C. von Mering, N. Zamboni
AbstractStudents will study bioinformatic concepts in the areas of metagenomics, genomics, transcriptomics, proteomics, biological networks and biostatistics. Through integrated lectures, practical hands-on exercises and project work, students will also be trained in analytical and programming skills to meet the emerging increase in data-driven knowledge generation in biology in the 21st century.
ObjectiveStudents will have an advanced understanding of the underlying concepts behind modern bioinformatic analyses at genome, metagenome and proteome-wide scales. They will be familiar with the most common data types, where to access them, and how to analytically work with them to address contemporary questions in the field of biology.
Prerequisites / NoticeCourse participants have already acquired basic programming skills in UNIX, Python and R.

Students bring their own computer with keyboard, internet access (browser) and software to connect to the ETH network via VPN.
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Media and Digital Technologiesassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered