Name | Prof. Dr. Nicola Zamboni |
Address | Inst. f. Molekulare Systembiologie ETH Zürich, HPM H 45 Otto-Stern-Weg 3 8093 Zürich SWITZERLAND |
Telephone | +41 44 633 31 41 |
zamboni@imsb.biol.ethz.ch | |
Department | Biology |
Relationship | Adjunct Professor |
Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|
551-0130-00L | Fundamentals of Biology II Registrations via myStudies until 2.2.2022 at the latest. Subsequent registrations will not be considered. | 8 credits | 8P | M. Gstaiger, N. Aceto, J. A. Antunes Pereira, M. Cangkrama, H. Gehart, Z. Kontarakis, W. Kovacs, A. Leitner, S. L. Masneuf, P. Picotti, U. Sauer, E. B. Truernit, A. Wutz, N. Zamboni | |
Abstract | This introductory Laboratory course introduces the student to the entire range of classical and modern molecular biosciences. In the second year (Praktikum GL Bio II) the students will perform three praktikum days in: - Plant Biology - Animal Models - Genomics - Molecular Systems Biology (total of 12 experiments) Each experiment takes one full day. | ||||
Learning objective | Introduction to theoretical and experimental biology General Praktikum-information and course material: Moodle The general Praktikum information (Assignment list, Instructions and Schedule & Performance Sheet) will also be sent to the students directly (E-mail). | ||||
Content | The class is divided into four blocks: Cell Biology, Plant Biology, Genomics AND Molecular Systems Biology. One block lasts three weeks. Animal Models: - Tissue structure and biology - Mouse anatomy and histology - Tissue repair and cancer GENOMICS: - Chromosome preparations from mammalian cells - Genome Editing - Cancer genomics Molecular Systems Biology: - Preparation of proteomics and metabolomics samples - Analysis of proteomics and metabolomics data - Interpretation of proteomics and metabolomics data PLANT BIOLOGY: - Plants and light - Phytohormones and other growth factors - Molecular biology of systemic gene silencing | ||||
Lecture notes | Laboratory manuals All scripts and additional course information is available on Moodle. | ||||
Prerequisites / Notice | THE PRAKTIKUM RULES: Your attendance is obligatory and you have to attend all 12 Praktikum days. Absences are only acceptable if you are able to provide a Doctor’s certificate. The original Dr's certificate has to be given to Dr. M. Gstaiger (HPM F43) within five days of the absence of the Praktikum day. If there will be any exceptional or important situations then you should directly contact the Director of Studies of D-Biol, who will decide if you are allowed to miss a Praktikum day or not. HIGHLY IMPORTANT!! 1. Due to the increased number of students, the official Praktikum registration has to be done, using myStudies, preferably at the end of HS21 but not later than 2.2.2022. 2. Later registration is NOT possible and can NOT be accepted! 3. The course registration for FS22 is usually possible at the end of HS21 and you will obtain an E-mail from the Rectorate when the course registration using myStudies is possible. Students can register for a practice group via myStudies. As soon as the course unit is registered in myStudies, a text box appears indicating that a group can be selected. Accordingly, students can select a group in the next step. If more than 180 students register, the surplus students will be placed on a waiting list and then allocated by the course responsible. The Praktikum GL BioII FS22 will take place during the following days and therefore, you have to make sure already now that you do not have any other activities & commitments during these days: PRAKTIKUM DAYS DURING FS22 (Monday): 21.02.; 28.02.; 07.03.; 14.03.; 21.03.; 28.03.; 04.04.; 11.04.; 02.05.; 09.05.; 16.05.; 23.05.; No Praktikum during the Easter break: 18.04-29.04. | ||||
551-0342-00L | Metabolomics Number of participants limited to 15. The enrolment is done by the D-BIOL study administration. | 6 credits | 7P | N. Zamboni, U. Sauer | |
Abstract | The course covers all basic aspects of metabolome measurements, from sample sampling to mass spectrometry and data analysis. Participants work in groups and independently perform and interpret metabolomic experiments. | ||||
Learning objective | Performing and reporting a metabolomic experiment, understanding pro and cons of mass spectrometry based metabolomics. Knowledge of workflows and tools to assist experiment interpretation, and metabolite identification. | ||||
Content | Basics of metabolomics: workflows, sample preparation, targeted and untargeted mass spectrometry, instrumentation, separation techniques (GC, LC, CE), metabolite identification, data interpretation and integration, normalization, QCs, maintenance. Soft skills to be trained: project planning, presentation, reporting, independent working style, team work. | ||||
551-0364-00L | Functional Genomics Information for UZH students: Enrolment to this course unit only possible at ETH. No enrolment to module BIO 254 at UZH. Please mind the ETH enrolment deadlines for UZH students: Link | 3 credits | 2V | C. von Mering, B. Bodenmiller, M. Gstaiger, H. Rehrauer, R. Schlapbach, K. Shimizu, N. Zamboni, further lecturers | |
Abstract | Functional genomics is key to understanding the dynamic aspects of genome function and regulation. Functional genomics approaches use the wealth of data produced by large-scale DNA sequencing, gene expression profiling, proteomics and metabolomics. Today functional genomics is becoming increasingly important for the generation and interpretation of quantitative biological data. | ||||
Learning objective | Functional genomics is key to understanding the dynamic aspects of genome function and regulation. Functional genomics approaches use the wealth of data produced by large-scale DNA sequencing, gene expression profiling, proteomics and metabolomics. Today functional genomics is becoming increasingly important for the generation and interpretation of quantitative biological data. Such data provide the basis for systems biology efforts to elucidate the structure, dynamics and regulation of cellular networks. | ||||
Content | The curriculum of the Functional Genomics course emphasizes an in depth understanding of new technology platforms for modern genomics and advanced genetics, including the application of functional genomics approaches such as advanced sequencing, proteomics, metabolomics, clustering and classification. Students will learn quality controls and standards (benchmarking) that apply to the generation of quantitative data and will be able to analyze and interpret these data. The training obtained in the Functional Genomics course will be immediately applicable to experimental research and design of systems biology projects. | ||||
Prerequisites / Notice | The Functional Genomics course will be taught in English. | ||||
551-1174-00L | Systems Biology | 5 credits | 2V + 2U | U. Sauer, S. Brüningk, J. Stelling, N. Zamboni | |
Abstract | The course teaches computational methods and first hands-on applications by starting from biological problems/phenomena that students in the 4th semester are somewhat familiar with. During the exercises, students will obtain first experience with programming their own analyses/models for data analysis/interpretation. | ||||
Learning objective | We will teach little if any novel biological knowledge or analysis methods, but focus on training the ability of use existing knowledge (for example from enzyme kinetics, regulatory mechanisms or analytical methods) to understand biological problems that arise when considering molecular elements in their context and to translate some of these problems into a form that can be solved by computational methods. Specific goals are: - understand the limitations of intuitive reasoning - obtain a first overview of computational approaches in systems biology - train ability to translate biological problems into computational problems - solve practical problems by programming with MATLAB - make first experiences in computational interpretation of biological data - understand typical abstractions in modeling molecular systems | ||||
Content | During the first 7 weeks, the will focus on mechanistic modeling. Starting from simple enzyme kinetics, we will move through the dynamics of small pathways that also include regulation and end with flux balance analysis of a medium size metabolic network. During the second 7 weeks, the focus will shift to the analysis of larger data sets, such as metabolomics and transcriptomics that are often generated in biology. Here we will go through multivariate statistical methods that include clustering and principal component analysis, ending with first methods to learn networks from data. | ||||
Lecture notes | Scripts to prepare the lectures will be provided via Moodle | ||||
Literature | The course is not taught by a particular book, but two books are suggested for further reading: - Systems Biology (Klipp, Herwig, Kowald, Wierling und Lehrach) Wiley-VCH 2009 - A First Course in Systems Biology (Eberhardt O. Voight) Garland Science 2012 |