Shinichi Sunagawa: Catalogue data in Autumn Semester 2023 |
| Name | Prof. Dr. Shinichi Sunagawa |
| Field | Microbiome Research |
| Address | Institut für Mikrobiologie ETH Zürich, HCI F 417 Vladimir-Prelog-Weg 1-5/10 8093 Zürich SWITZERLAND |
| Telephone | +41 44 633 61 55 |
| ssunagawa@ethz.ch | |
| URL | http://www.micro.biol.ethz.ch/research/sunagawa.html |
| Department | Biology |
| Relationship | Associate Professor |
| Number | Title | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 551-1109-00L | Seminars in Microbiology | 0 credits | 2K | S. Sunagawa, W.‑D. Hardt, M. Künzler, J. Piel, J. Vorholt-Zambelli | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Seminars by invited speakers covering selected microbiology themes. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Discussion of selected microbiology themes presented by invited speakers. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 551-1119-00L | Microbial Community Genomics  Number of participants limited to 10. Prerequisites: Participants should bring their own laptop computer. Basic knowledge in [R], Python and/or UNIX is required. The enrolment is done by the D-BIOL study administration. | 6 credits | 7P | S. Sunagawa | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | We provide training in the use of computational methods to address molecular, genetic, ecological and/or evolutionary questions by analyzing DNA sequencing data from microbial communities. The course includes lectures, tutorials, and the development of a research project at the intersection between microbiology and bioinformatics. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students will learn concepts and methods for analyzing complex 'omics' datasets and applying them in individual projects. To facilitate learning, the course includes lectures on functional genomics, metagenomics and microbiology, along with practical sessions on scientific programming to analyze and visualize biological data. Additionally, students will learn how to plan, execute, report on, and present a scientific project. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Participants should bring their own laptop computer. Basic knowledge in [R], Python and/or UNIX is required. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competencies |
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| 551-1299-00L | Bioinformatics | 6 credits | 4G | S. Sunagawa, P. Beltrao, V. Boeva, A. Kahles, C. von Mering, N. Zamboni | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Students 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Students 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 / Notice | Course 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. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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