Berend Snijder: Catalogue data in Autumn Semester 2020 |
Name | Prof. Dr. Berend Snijder |
Field | Molecular Systems Biology |
Address | Inst. f. Molekulare Systembiologie ETH Zürich, HPM H 44 Otto-Stern-Weg 3 8093 Zürich SWITZERLAND |
Telephone | +41 44 633 71 49 |
snijder@imsb.biol.ethz.ch | |
URL | http://www.snijderlab.org |
Department | Biology |
Relationship | Assistant Professor |
Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|
551-1299-00L | Introduction to Bioinformatics | 6 credits | 4G | S. Sunagawa, M. Gstaiger, A. Kahles, G. Rätsch, B. Snijder, E. Vayena, C. von Mering, N. Zamboni | |
Abstract | This course introduces principle concepts, the state-of-the-art and methods used in some major fields of Bioinformatics. Topics include: genomics, metagenomics, network bioinformatics, and imaging. Lectures are accompanied by practical exercises that involve the use of common bioinformatic methods and basic programming. | ||||
Learning objective | The course will provide students with theoretical background in the area of genomics, metagenomics, network bioinformatics and imaging. In addition, students will acquire basic skills in applying modern methods that are used in these sub-disciplines of Bioinformatics. Students will be able to access and analyse DNA sequence information, construct and interpret networks that emerge though interactions of e.g. genes/proteins, and extract information based on computer-assisted image data analysis. Students will also be able to assess the ethical implications of access to and generation of new and large amounts of information as they relate to the identifiability of a person and the ownership of data. | ||||
Content | Ethics: Case studies to learn about applying ethical principles in human genomics research Genomics: Genetic variant calling Analysis and critical evaluation of genome wide association studies Metagenomics: Reconstruction of microbial genomes Microbial community compositional analysis Quantitative metagenomics Network bioinformatics: Inference of molecular networks Use of networks for interpretation of (gen)omics data Imaging: High throughput single cell imaging Image segmentation Automatic analysis of drug effects on single cell suspension (chemotyping) | ||||
Prerequisites / Notice | Course participants have already acquired basic programming skills in Python and R. Students will bring and work on their own laptop computers, preferentially running the latest versions of Windows or MacOSX. | ||||
551-1303-00L | Cellular Biochemistry of Health and Disease Number of participants limited to 20. | 4 credits | 2S | V. Korkhov, Y. Barral, T. Ishikawa, M. Jagannathan, R. Kroschewski, G. Neurohr, M. Peter, A. E. Smith, B. Snijder, K. Weis | |
Abstract | During this Masters level seminar style course, students will explore current research topics in cellular biochemistry focused on the structure, function and regulation of selected cell components, and the consequences of dysregulation for pathologies. | ||||
Learning objective | Students will work with experts toward a critical analysis of cutting-edge research in the domain of cellular biochemistry, with emphasis on normal cellular processes and the consequences of their dysregulation. At the end of the course, students will be able to introduce, present, evaluate, critically discuss and write about recent scientific articles in the research area of cellular biochemistry. | ||||
Content | Guided by an expert in the field, students will engage in classical round-table style discussions of current literature with occasional frontal presentations. Students will alternate as discussion leaders throughout the semester, with the student leader responsible to briefly summarize key general knowledge and context of the assigned primary research paper. Together with the faculty expert, all students will participate in discussion of the primary paper, including the foundation of the biological question, specific questions addressed, key methods, key results, remaining gaps and research implications. | ||||
Literature | The literature will be provided during the course | ||||
Prerequisites / Notice | The course will be taught in English. | ||||
551-1415-00L | Image-based Drug Screening in Human Blood for Personalized Medicine Number of participants limited to 5. The enrolment is done by the D-BIOL study administration. General safety regulations for all block courses: -Whenever possible the distance rules have to be respected -All students have to wear masks throughout the course (keep reserve masks ready) -The installation and activation of the Swiss Covid-App is highly encouraged -Any additional rules for individual courses have to be respected -Students showing any COVID-19 symptoms are not allowed to enter ETH buildings and have to inform the course responsible | 6 credits | 7P | B. Snijder, further lecturers | |
Abstract | Image based screening allows to measure in high throughput the phenotype of millions of individual cells to external perturbations. We have recently shown that image-based screening in human blood can help to find active treatments for patients with blood cancers. In this course we will take the students through the entire workflow (to the extent that biosafety regulations allow it). | ||||
Learning objective | Take the students through the entire workflow from experimental design, to screen, to imaging and analysis. -Learn to design an image-based screening experiment -Observe human blood sample handling -Perform immunofluorescence & automated confocal microscopy -Image analysis and result interpretation -Result presentation | ||||
Literature | -Relevant study: https://www.thelancet.com/journals/lanhae/article/PIIS2352-3026(17)30208-9/fulltext -Editorial commentary: https://www.thelancet.com/journals/lanhae/article/PIIS2352-3026(17)30213-2/fulltext |