Search result: Catalogue data in Autumn Semester 2023
Biology Master  | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 Master Studies (Programme Regulations 2023) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Major in Molecular and Structural Biology | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Elective Compulsory Master Courses | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 551-1401-00L | Advanced Protein Engineering (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: BCH420 Restricted to max.10 students from ETH Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/deadlines.html | W | 2 credits | 2G | University lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Introduction into current research strategies in protein science. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | To understand current research strategies in protein science. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Proteins have become an object of intense study in modern science, raging from their use as therapeutics to elucidating their structure and function in the cell. Moreover, it is now possible to engineer and evolve tailor-made proteins, opening up many new areas of science. This course will attempt to cover the frontiers and remaining challenges, emphasizing the biochemical foundations of the various approaches. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Slides and references will be available on OLAT server. https://www.olat.uzh.ch/olat/auth/repo/go?rid=600670219 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | PDFs will be available on OLAT server. https://www.olat.uzh.ch/olat/auth/repo/go?rid=600670219 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Solid knowledge in biochemistry strongly recommended | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 551-1153-00L | Systems Biology of Metabolism Number of participants limited to 15. | W | 4 credits | 2V | U. Sauer, N. Zamboni | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Starting 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Develop a deeper understanding of how relevant biological problems can be solved, thereby providing advanced insights to key experimental and computational methods in systems biology. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The 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 notes | Script and original publications will be supplied during the course. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 529-0004-01L | Classical Simulation of (Bio)Molecular Systems | W | 6 credits | 4G | P. H. Hünenberger, J. Dolenc, S. Riniker | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Molecular models, classical force fields, configuration sampling, molecular dynamics simulation, boundary conditions, electrostatic interactions, analysis of trajectories, free-energy calculations, structure refinement, applications in chemistry and biology. Exercises: hands-on computer exercises for learning progressively how to perform an analyze classical simulations (using the package GROMOS). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Introduction to classical (atomistic) computer simulation of (bio)molecular systems, development of skills to carry out and interpret these simulations. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Molecular models, classical force fields, configuration sampling, molecular dynamics simulation, boundary conditions, electrostatic interactions, analysis of trajectories, free-energy calculations, structure refinement, applications in chemistry and biology. Exercises: hands-on computer exercises for learning progressively how to perform an analyze classical simulations (using the package GROMOS). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | The powerpoint slides of the lectures will be made available weekly on the website in pdf format (on the day preceding each lecture). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | See: www.csms.ethz.ch/education/CSBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Since the exercises on the computer do convey and test essentially different skills than those being conveyed during the lectures and tested at the oral exam, the results of the exercises are taken into account when evaluating the results of the exam (learning component, possible bonus of up to 0.25 points on the exam mark). For more information about the lecture: www.csms.ethz.ch/education/CSBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competencies |
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| 401-0649-00L | Applied Statistical Regression | W | 5 credits | 2V + 1U | M. Dettling | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course offers a practically oriented introduction into regression modeling methods. The basic concepts and some mathematical background are included, with the emphasis lying in learning "good practice" that can be applied in every student's own projects and daily work life. A special focus will be laid in the use of the statistical software package R for regression analysis. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course starts with the basics of linear modeling, and then proceeds to parameter estimation, tests, confidence intervals, residual analysis, model choice, and prediction. More rarely touched but practically relevant topics that will be covered include variable transformations, multicollinearity problems and model interpretation, as well as general modeling strategies. The last third of the course is dedicated to an introduction to generalized linear models: this includes the generalized additive model, logistic regression for binary response variables, binomial regression for grouped data and poisson regression for count data. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | A script will be available. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Faraway (2005): Linear Models with R Faraway (2006): Extending the Linear Model with R Draper & Smith (1998): Applied Regression Analysis Fox (2008): Applied Regression Analysis and GLMs Montgomery et al. (2006): Introduction to Linear Regression Analysis | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The exercises, but also the classes will be based on procedures from the freely available, open-source statistical software package R, for which an introduction will be held. In the Mathematics Bachelor and Master programmes, the two course units 401-0649-00L "Applied Statistical Regression" and 401-3622-00L "Statistical Modelling" are mutually exclusive. Registration for the examination of one of these two course units is only allowed if you have not registered for the examination of the other course unit. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 401-6215-00L | Using R for Data Analysis and Graphics (Part I)  | W | 1.5 credits | 1G | M. Mächler | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | The course provides the first part an introduction to the statistical/graphical/data science software R (https://www.r-project.org/) for scientists. Topics covered are data generation and selection, graphical and basic statistical functions, creating simple functions, basic types of objects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The students will be able to use the software R for simple data analysis and graphics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The course provides the first part of an introduction to the statistical software R for scientists. R is free software that contains a huge collection of functions with focus on statistics and graphics. If one wants to use R one has to learn the programming language R - on very rudimentary level. The course aims to facilitate this by providing a basic introduction to R. Part I of the course covers the following topics: - What is R? - R Basics: reading and writing data from/to files, creating vectors & matrices, selecting elements of dataframes, vectors and matrices, arithmetics; - Types of data: numeric, character, logical and categorical data, missing values; - Simple (statistical) functions: summary, mean, var, etc., simple statistical tests; - Writing simple functions; - Introduction to graphics: scatter-, boxplots and other high-level plotting functions, embellishing plots by title, axis labels, etc., adding elements (lines, points) to existing plots. The course focuses on practical work at the computer with R. We will make use of the graphical user interface RStudio: www.rstudio.org Note: Part I of UsingR is complemented and extended by Part II, which is offered during the second part of the semester and which can be taken independently from Part I. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | An Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | The course resources will be provided via the Moodle web learning platform. Subscribing via Mystudies *automatically* makes you a student participant of the Moodle course of this lecture, which is at https://moodle-app2.let.ethz.ch/course/view.php?id=20847 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 529-0041-00L | Modern Mass Spectrometry, Hyphenated Methods, and Chemometrics | W | 6 credits | 3G | R. Zenobi, B. Hattendorf, P. Sinués Martinez-Lozano | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Modern mass spectrometry, hyphenated analytical methods, speciation, chemometrics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Comprehensive knowledge about the analytical methods introduced in this course and their practical applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Hyphenation of separation with identification methods such as GC-MS, LC-MS, GC-IR, LC-IR, LC-NMR etc.; importance of speciation. Modern mass spectrometry: time-of-flight, orbitrap and ion cyclotron resonance mass spectrometry, ICP-MS. Soft ionization methods, desorption methods, spray methods. Mass spectrometry imaging. Use of statistical and computer-assisted methods for processing analytical data (chemometrics). | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | Lecture notes will be made available online. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Information about relevant literature will be available in the lecture & in the lecture notes. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Exercises are an integral part of the lecture. Prerequisites: 529-0051-00 "Analytische Chemie I (3. Semester)" 529-0058-00 "Analytische Chemie II (4. Semester)" (or equivalent) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 551-1407-00L | RNA Biology Lecture Series I: Transcription & Processing & Translation Does not take place this semester. | W | 4 credits | 2V | F. Allain, N. Ban, S. Jonas, U. Kutay, further lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course covers aspects of RNA biology related to gene expression at the posttranscriptional level. These include RNA transcription, processing, alternative splicing, editing, export and translation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The students should obtain an understanding of these processes, which are at work during gene expression. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Transcription & 3'end formation ; splicing, alternative splicing, RNA editing; the ribosome & translation, translation regulation, RNP biogenesis & nuclear export, mRNA surveillance & mRNA turnover; signal transduction & RNA. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Basic knowledge of cell and molecular biology. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 551-1409-00L | RNA Biology Lecture Series II: Non-Coding RNAs: Biology and Therapeutics | W | 4 credits | 2V | J. Hall, M. Stoffel, further lecturers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | This course covers aspects of RNA biology related to the functions of non-coding RNAs as well as their use as drugs to treat diseases. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | The students should get familiar with the wide array of roles, which non-coding RNAs play in cellular functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | Micro RNAs; computational approaches to miRNAs; micro RNA function in metabolism; viruses and viral RNAs; nucleic acid-based drugs; ncRNA-mediated genome regulation; epigenetic programming of genome remodelling in ciliates; telomerase and telomeres; tRNA biology. http://www.nccr-rna-and-disease.ch/tiki-index.php?page=LectureSeries | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Basic knowledge of cell and molecular biology. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 227-0939-00L | Cell Biophysics | W | 6 credits | 4G | T. Zambelli | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Applying two fundamental principles of thermodynamics (entropy maximization and Gibbs energy minimization), an analytical model is derived for a variety of biological phenomena at the molecular as well as cellular level, and critically compared with the corresponding experimental data in the literature. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | Engineering uses the laws of physics to predict the behavior of a system. Biological systems are so diverse and complex prompting the question whether we can apply unifying concepts of theoretical physics coping with the multiplicity of life’s mechanisms. Objective of this course is to show that biological phenomena despite their variety can be analytically described using only two principles from statistical mechanics: maximization of the entropy and minimization of the Gibbs free energy. Starting point of the course is the probability theory, which enables to derive step-by-step the two pillars of thermodynamics from the perspective of statistical mechanics: the maximization of entropy according to the Boltzmann’s law as well as the minimization of the Gibbs free energy. Then, an assortment of biological phenomena at the molecular and cellular level (e.g. cytoskeletal polymerization, action potential, photosynthesis, gene regulation, morphogen patterning) will be examined at the light of these two principles with the aim to derive a quantitative expression describing their behavior. Each analytical model is finally validated by comparing it with the corresponding experimental results from the literature. By the end of the course, students will also learn to critically evaluate the concepts of making an assumption and making an approximation. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | • Basics of theory of probability • Boltzmann's law • Entropy maximization and Gibbs free energy minimization • Ligand-receptor: two-state systems and the MWC model • Random walks, diffusion, crowding • Electrostatics for salty solutions • Elasticity: fibers and membranes • Molecular motors • Action potential: Hodgkin-Huxley model • Photosynthesis and vision • Gene regulation • Development: Turing patterns Theory and corresponding exercises are merged together during the classes. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | No lecture notes because the two proposed textbooks are more than exhaustive! An extra hour (Mon 17.00 o'clock - 18.00) will be proposed via ZOOM to solve together the exercises of the previous week. !!!!! I am using OneNote. All lectures and exercises will be broadcast via ZOOM (the link of the recordings will be available in Moodle on Fri, 22 Dec after the last lesson) !!!!! | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | • (Statistical Mechanics) K. Dill, S. Bromberg, "Molecular Driving Forces", 2nd Edition, Garland Science, 2010. • (Biophysics) R. Phillips, J. Kondev, J. Theriot, H. Garcia, "Physical Biology of the Cell", 2nd Edition, Garland Science, 2012. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Participants need a good command of • differentiation and integration of a function with one or more variables (basics of Analysis), • Newton's and Coulomb's laws (basics of Mechanics and Electrostatics). Notions of vectors in 2D and 3D are beneficial. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 529-0733-02L | Chemical Biology and Synthetic Biochemistry | W | 6 credits | 3G | K. Lang, M. Fottner | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Overview of modern chemical biology and synthetic biochemistry techniques, focussed on protein modification and labeling and on methods to endow proteins with novel functionalities. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After taking this course, students should be capable of the following: A) Recall different possibilities for modifying proteins in vitro and in vivo and their applications in a biological context, B) Understand the chemical and biochemical consequences of modifications and assess the different reaction possibilities in the context of in vivo - in vitro, C) Critically analyze and assess current chemical biology articles D) Question the approaches learned and apply them to new biological problems. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | principles of protein labeling and protein modification (fluorescent proteins, enzyme-mediated labeling, bioorthogonal chemistries) advanced genetic code expansion methods (amber suppression, orthogonal ribosomes, unnatural base pairs, genome engineering and genome editing) directed evolution and protein engineering chemical biology of ubiquitin and targeted protein degradation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Lecture notes | A script will not be handed out. Handouts to the lecture will be provided through moodle. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Citations from the original literature relevant to the individual lectures will be assigned during the lectures. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | Knowledge provided in the bachelor lectures 'Nucleic Acids and Carbohydrates' and 'Proteins and Lipids' is assumed for this lecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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