Search result: Catalogue data in Spring Semester 2021

Biology Master Information
Elective Major Subject Areas
Elective Major: Systems Biology
Compulsory Concept Courses
NumberTitleTypeECTSHoursLecturers
551-0324-00LSystems Biology Information O6 credits4VP. Picotti, M. Claassen, U. Sauer, B. Snijder, B. Wollscheid
AbstractIntroduction to experimental and computational methods of systems biology. By using baker’s yeast as a thread through the series, we focus on global methods for analysis of and interference with biological functions. Illustrative applications to other organisms will highlight medical and biotechnological aspects.
Objective- obtain an overview of global analytical methods
- obtain an overview of computational methods in systems biology
- understand the concepts of systems biology
ContentOverview of global analytical methods (e.g. DNA arrays, proteomics, metabolomics, fluxes etc), global interference methods (siRNA, mutant libraries, synthetic lethality etc.) and imaging methods. Introduction to mass spectrometry and proteomics. Concepts of metabolism in microbes and higher cells. Systems biology of developmental processes. Concepts of mathematical modeling and applications of computational systems biology.
Lecture notesno script
LiteratureThe course is not taught by a particular book, but some books are suggested for further reading:

- Systems biology in Practice by Klipp, Herwig, Kowald, Wierling und Lehrach. Wiley-VCH 2005
Elective Compulsory Concept Courses
See D-BIOL Master Studies Guide
NumberTitleTypeECTSHoursLecturers
551-0320-00LCellular Biochemistry (Part II)W3 credits2VY. Barral, R. Kroschewski, A. E. Smith
AbstractThis course will focus on molecular mechanisms and concepts underlying cellular biochemistry, providing advanced insights into the structural and functional details of individual cell components, and the complex regulation of their interactions. Particular emphasis will be on the spatial and temporal integration of different molecules and signaling pathways into global cellular processes.
ObjectiveThe full-year course (551-0319-00 & 551-0320-00) focuses on the molecular mechanisms and concepts underlying the biochemistry of cellular physiology, investigating how these processes are integrated to carry out highly coordinated cellular functions. The molecular characterization of complex cellular functions requires a combination of approaches such as biochemistry, but also cell biology and genetics. This course is therefore the occasion to discuss these techniques and their integration in modern cellular biochemistry.
The students will be able to describe the structural and functional details of individual cell components, and the spatial and temporal regulation of their interactions. In particular, they will learn to explain how different molecules and signaling pathways can be integrated during complex and highly dynamic cellular processes such as intracellular transport, cytoskeletal rearrangements, cell motility, and cell division. In addition, they will be able to illustrate the relevance of particular signaling pathways for cellular pathologies such as cancer or during cellular infection.
ContentSpatial and temporal integration of different molecules and signaling pathways into global cellular processes, such as cell division, cell infection and cell motility. Emphasis is also put on the understanding of pathologies associated with defective cell physiology, such as cancer or during cellular infection.
LiteratureRecommended supplementary literature may be provided during the course.
Prerequisites / NoticeTo attend this course the students must have a solid basic knowledge in chemistry, biochemistry, cell biology and general biology. Biology students have in general already attended the first part of the "Cellular Biochemistry" concept course (551-0319-00). The course will be taught in English.
In addition, the course will be based on a blended-learning scenario, where frontal lectures will be complemented with carefully chosen web-based teaching elements that students access through the ETH Moodle platform.
551-0314-00LMicrobiology (Part II)W3 credits2VW.‑D. Hardt, L. Eberl, J. Piel, J. Vorholt-Zambelli
AbstractAdvanced lecture class providing a broad overview on bacterial cell structure, genetics, metabolism, symbiosis and pathogenesis.
ObjectiveThis concept class will be based on common concepts and introduce to the enormous diversity among bacteria and archaea. It will cover the current research on bacterial cell structure, genetics, metabolism, symbiosis and pathogenesis.
ContentAdvanced class covering the state of the research in bacterial cell structure, genetics, metabolism, symbiosis and pathogenesis.
Lecture notesUpdated handouts will be provided during the class.
LiteratureCurrent literature references will be provided during the lectures.
Prerequisites / NoticeEnglish
Elective Compulsory Master Courses I: Computation
NumberTitleTypeECTSHoursLecturers
636-0702-00LStatistical Models in Computational BiologyW6 credits2V + 1U + 2AN. Beerenwinkel
AbstractThe course offers an introduction to graphical models and their application to complex biological systems. Graphical models combine a statistical methodology with efficient algorithms for inference in settings of high dimension and uncertainty. The unifying graphical model framework is developed and used to examine several classical and topical computational biology methods.
ObjectiveThe goal of this course is to establish the common language of graphical models for applications in computational biology and to see this methodology at work for several real-world data sets.
ContentGraphical models are a marriage between probability theory and graph theory. They combine the notion of probabilities with efficient algorithms for inference among many random variables. Graphical models play an important role in computational biology, because they explicitly address two features that are inherent to biological systems: complexity and uncertainty. We will develop the basic theory and the common underlying formalism of graphical models and discuss several computational biology applications. Topics covered include conditional independence, Bayesian networks, Markov random fields, Gaussian graphical models, EM algorithm, junction tree algorithm, model selection, Dirichlet process mixture, causality, the pair hidden Markov model for sequence alignment, probabilistic phylogenetic models, phylo-HMMs, microarray experiments and gene regulatory networks, protein interaction networks, learning from perturbation experiments, time series data and dynamic Bayesian networks. Some of the biological applications will be explored in small data analysis problems as part of the exercises.
Lecture notesno
Literature- Airoldi EM (2007) Getting started in probabilistic graphical models. PLoS Comput Biol 3(12): e252. doi:10.1371/journal.pcbi.0030252
- Bishop CM. Pattern Recognition and Machine Learning. Springer, 2007.
- Durbin R, Eddy S, Krogh A, Mitchinson G. Biological Sequence Analysis. Cambridge university Press, 2004
401-0102-00LApplied Multivariate StatisticsW5 credits2V + 1UF. Sigrist
AbstractMultivariate statistics analyzes data on several random variables simultaneously. This course introduces the basic concepts and provides an overview of classical and modern methods of multivariate statistics including visualization, dimension reduction, supervised and unsupervised learning for multivariate data. An emphasis is on applications and solving problems with the statistical software R.
ObjectiveAfter the course, you are able to:
- describe the various methods and the concepts behind them
- identify adequate methods for a given statistical problem
- use the statistical software R to efficiently apply these methods
- interpret the output of these methods
ContentVisualization, multivariate outliers, the multivariate normal distribution, dimension reduction, principal component analysis, multidimensional scaling, factor analysis, cluster analysis, classification, multivariate tests and multiple testing
Lecture notesNone
Literature1) "An Introduction to Applied Multivariate Analysis with R" (2011) by Everitt and Hothorn
2) "An Introduction to Statistical Learning: With Applications in R" (2013) by Gareth, Witten, Hastie and Tibshirani

Electronic versions (pdf) of both books can be downloaded for free from the ETH library.
Prerequisites / NoticeThis course is targeted at students with a non-math background.

Requirements:
==========
1) Introductory course in statistics (min: t-test, regression; ideal: conditional probability, multiple regression)
2) Good understanding of R (if you don't know R, it is recommended that you study chapters 1,2,3,4, and 5 of "Introductory Statistics with R" from Peter Dalgaard, which is freely available online from the ETH library)

An alternative course with more emphasis on theory is 401-6102-00L "Multivariate Statistics" (only every second year).

401-0102-00L and 401-6102-00L are mutually exclusive. You can register for only one of these two courses.
227-0396-00LEXCITE Interdisciplinary Summer School on Bio-Medical Imaging Restricted registration - show details
The school admits 60 MSc or PhD students with backgrounds in biology, chemistry, mathematics, physics, computer science or engineering based on a selection process.

Students have to apply for acceptance. To apply a curriculum vitae and an application letter need to be submitted.
Further information can be found at: www.excite.ethz.ch.
W4 credits6GS. Kozerke, G. Csúcs, J. Klohs-Füchtemeier, S. F. Noerrelykke, M. P. Wolf
AbstractTwo-week summer school organized by EXCITE (Center for EXperimental & Clinical Imaging TEchnologies Zurich) on biological and medical imaging. The course covers X-ray imaging, magnetic resonance imaging, nuclear imaging, ultrasound imaging, optoacoustic imaging, infrared and optical microscopy, electron microscopy, image processing and analysis.
ObjectiveStudents understand basic concepts and implementations of biological and medical imaging. Based on relative advantages and limitations of each method they can identify preferred procedures and applications. Common foundations and conceptual differences of the methods can be explained.
ContentTwo-week summer school on biological and medical imaging. The course covers concepts and implementations of X-ray imaging, magnetic resonance imaging, nuclear imaging, ultrasound imaging, optoacoustic imaging, infrared and optical microscopy and electron microscopy. Multi-modal and multi-scale imaging and supporting technologies such as image analysis and modeling are discussed. Dedicated modules for physical and life scientists taking into account the various backgrounds are offered.
Lecture notesPresentation slides, Web links
Prerequisites / NoticeThe school admits 60 MSc or PhD students with backgrounds in biology, chemistry, mathematics, physics, computer science or engineering based on a selection process. To apply a curriculum vitae, a statement of purpose and applicants references need to be submitted. Further information can be found at: http://www.excite.ethz.ch/education/summer-school.html
Elective Compulsory Master Courses II: Biology
NumberTitleTypeECTSHoursLecturers
551-1310-00LA Problem-Based Approach to Cellular Biochemistry Restricted registration - show details
Number of participants limited to 12.
W6 credits2GM. Peter, V. Korkhov, G. Neurohr, V. Panse, A. E. Smith, F. van Drogen
AbstractIndependent, guided acquisition of a defined area of research, identification of key open questions, development of an experimental strategy to address a defined question, and formulation of this strategy within the framework of a research grant.
ObjectiveWorking independently, students will acquire an overview of a defined research area, and identify important open questions. In addition, they will develop an experimental strategy to address a defined question, and to formulate this strategy within the framework of a research grant.
ContentThe students will work in groups of two to three, in close contact with a tutor (ETH Prof or senior scientist). A research overview with open questions and a research grant will be developed independently by the students, with guidance from the tutor through regular mandatory meetings. The students will write both the research overview with open questions and the grant in short reports, and present them to their colleagues.
LiteratureThe identification of appropriate literature is a component of the course.
Prerequisites / NoticeThis course will be taught in English, and requires extensive independent work.
551-0364-00LFunctional 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
W3 credits2VC. von Mering, C. Beyer, B. Bodenmiller, M. Gstaiger, H. Rehrauer, R. Schlapbach, K. Shimizu, N. Zamboni, further lecturers
AbstractFunctional 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.
ObjectiveFunctional 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.
ContentThe 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 / NoticeThe Functional Genomics course will be taught in English.
551-0224-00LAdvanced Proteomics Restricted registration - show details
For master students from the 2nd semester on, also doctoral candidates and post docs.
W4 credits6GP. Picotti, L. Gillet, A. Leitner, P. Pedrioli
AbstractGoal of the course is to analyze current and newly emerging technologies and approaches in protein and proteome analysis with regard to their application in biology, biotechnology and medicine.
Format: Introduction by instructor followed by discussions stimulated by reading assignments and exercises.
ObjectiveTo discuss current and newly emerging technologies and approaches in protein and proteome analysis with regard to their applications in biology, biotechnology, medicine and systems biology.
ContentBlock course teaching current methods for the acquisition and processing of proteomic datasets.
Prerequisites / NoticeNumber of people: Not exceeding 30.
Students from ETHZ, Uni Zurich and University of Basel
Non-ETH students must register at ETH Zurich as special students http://www.rektorat.ethz.ch/students/admission/auditors/index_EN
701-1418-00LModelling Course in Population and Evolutionary Biology Information Restricted registration - show details
Number of participants limited to 20.

Priority is given to MSc Biology and Environmental Sciences students.
W4 credits6PS. Bonhoeffer, V. Müller
AbstractThis course provides a "hands-on" introduction into mathematical/computational modelling of biological processes with particular emphasis on evolutionary and population-biological questions. The models are developed using the Open Source software R.
ObjectiveThe aim of this course is to provide a practical introduction into the modelling of fundamental biological questions. The participants will receive guidance to develop mathematical/computational models in small teams. The participants chose two modules with different levels of difficulty from a list of projects.

The participant shall get a sense of the utility of modelling as a tool to investigate biological problems. The simpler modules are based mostly on examples from the earlier lecture "Ecology and evolution: populations" (script accessible at the course webpage). The advanced modules address topical research questions. Although being based on evolutionary and population biological methods and concepts, these modules also address topics from other areas of biology.
Contentsee www.tb.ethz.ch/education/learningmaterials/modelingcourse.html
Lecture notesDetailed handouts describing both the modelling and the biological background are available to each module at the course website. In addition, the script of the earlier lecture "Ecology and evolution: populations" can also be downloaded, and contains further background information.
Prerequisites / NoticeThe course is based on the open source software R. Experience with R is useful but not required for the course. Similarly, the course 701-1708-00L Infectious Disease Dynamics is useful but not required.
551-1126-00LTechnologies in Molecular MicrobiologyW4 credits2VB. Nguyen, W.‑D. Hardt, further lecturers
AbstractThe lecture course provides an advanced understanding of modern techniques used in molecular microbiology. Current technologies and research directions in molecular microbiology including applied aspects will be illustrated with paper discussions. The format is a lecture course enriched by group activities.
ObjectiveThe lecture course aims at providing principles of modern techniques used in molecular microbiology. Emphasis is on genetic, biochemical, cellular, and community analysis . Discussion of a set of commonly applied technologies will assist students in evaluating current research in molecular microbiology and choosing appropriate methods for their own demands.
ContentImportant genetic, biochemical, biophysical, and community analysis methods will be presented that are used to gain a deeper understanding of the molecular principles and mechanisms underlying basic physiological processes in prokaryotes. Applied aspects of molecular microbiology and current research in this area will also be covered.

List of topics:
- Analysis of genes, genomes and transcriptomes
- Analysis of proteins, proteomes and microbial systems
Lecture notesUpdated handouts will be provided during the class.
LiteratureCurrent literature references, relevant papers and handouts will be provided during the lectures.
Prerequisites / NoticeThe following lecturers will contribute to the course:
Dr. Alex Brachmann (ETH)
Prof. Hans-Martin Fischer (ETH)
Dr. Florian Freimoser (Agroscope)
Dr. Jonas Grossmann (FGCZ)
Annika Hausmann (ETH)
Dr. Bidong Nguyen (ETH)
Dr. Bernd Roschitzki (FGCZ)
Dr. Roman Spörri (ETH)
701-1708-00LInfectious Disease DynamicsW4 credits2VS. Bonhoeffer, R. D. Kouyos, R. R. Regös, T. Stadler
AbstractThis course introduces into current research on the population biology of infectious diseases. The course discusses the most important mathematical tools and their application to relevant diseases of human, natural or managed populations.
ObjectiveAttendees will learn about:
* the impact of important infectious pathogens and their evolution on human, natural and managed populations
* the population biological impact of interventions such as treatment or vaccination
* the impact of population structure on disease transmission

Attendees will learn how:
* the emergence spread of infectious diseases is described mathematically
* the impact of interventions can be predicted and optimized with mathematical models
* population biological models are parameterized from empirical data
* genetic information can be used to infer the population biology of the infectious disease

The course will focus on how the formal methods ("how") can be used to derive biological insights about the host-pathogen system ("about").
ContentAfter an introduction into the history of infectious diseases and epidemiology the course will discuss basic epidemiological models and the mathematical methods of their analysis. We will then discuss the population dynamical effects of intervention strategies such as vaccination and treatment. In the second part of the course we will introduce into more advanced topics such as the effect of spatial population structure, explicit contact structure, host heterogeneity, and stochasticity. In the final part of the course we will introduce basic concepts of phylogenetic analysis in the context of infectious diseases.
Lecture notesSlides and script of the lecture will be available online.
LiteratureThe course is not based on any of the textbooks below, but they are excellent choices as accompanying material:
* Keeling & Rohani, Modeling Infectious Diseases in Humans and Animals, Princeton Univ Press 2008
* Anderson & May, Infectious Diseases in Humans, Oxford Univ Press 1990
* Murray, Mathematical Biology, Springer 2002/3
* Nowak & May, Virus Dynamics, Oxford Univ Press 2000
* Holmes, The Evolution and Emergence of RNA Viruses, Oxford Univ Press 2009
Prerequisites / NoticeBasic knowledge of population dynamics and population genetics as well as linear algebra and analysis will be an advantage.
636-0111-00LSynthetic Biology I
Attention: This course was offered in previous semesters with the number: 636-0002-00L "Synthetic Biology I". Students that already passed course 636-0002-00L cannot receive credits for course 636-0111-00L.
W4 credits3GS. Panke, J. Stelling
AbstractTheoretical & practical introduction into the design of dynamic biological systems at different levels of abstraction, ranging from biological fundamentals of systems design (introduction to bacterial gene regulation, elements of transcriptional & translational control, advanced genetic engineering) to engineering design principles (standards, abstractions) mathematical modelling & systems desig
ObjectiveAfter the course, students will be able to theoretically master the biological and engineering fundamentals required for biological design to be able to participate in the international iGEM competition (see www.igem.ethz.ch).
ContentThe overall goal of the course is to familiarize the students with the potential, the requirements and the problems of designing dynamic biological elements that are of central importance for manipulating biological systems, primarily (but not exclusively) prokaryotic systems. Next, the students will be taken through a number of successful examples of biological design, such as toggle switches, pulse generators, and oscillating systems, and apply the biological and engineering fundamentals to these examples, so that they get hands-on experience on how to integrate the various disciplines on their way to designing biological systems.
Lecture notesHandouts during classes.
LiteratureMark Ptashne, A Genetic Switch (3rd ed), Cold Spring Haror Laboratory Press
Uri Alon, An Introduction to Systems Biology, Chapman & Hall
Prerequisites / Notice1) Though we do not place a formal requirement for previous participation in particular courses, we expect all participants to be familiar with a certain level of biology and of mathematics. Specifically, there will be material for self study available on https://bsse.ethz.ch/bpl/education/lectures/synthetic-biology-i/download.html as of mid January, and everybody is expected to be fully familiar with this material BEFORE THE CLASS BEGINS to be able to follow the different lectures. Please contact sven.panke@bsse.ethz.ch for access to material
2) The course is also thought as a preparation for the participation in the international iGEM synthetic biology summer competition (www.syntheticbiology.ethz.ch, http://www.igem.org). This competition is also the contents of the course Synthetic Biology II. https://bsse.ethz.ch/bpl/education/lectures/synthetic-biology-i/download.html
551-1103-00LMicrobial Biochemistry Information W4 credits2VJ. Vorholt-Zambelli, J. Piel
AbstractThe lecture course aims at providing an advanced understanding of the physiology and metabolism of microorganisms. Emphasis is on processes that are specific to bacteria and archaea and that contribute to the widespread occurrence of prokaryotes. Applied aspects of microbial biochemistry will be pointed out as well as research fields of current scientific interest.
ObjectiveThe lecture course aims at providing an advanced understanding of the physiology and metabolism of microorganisms.
ContentImportant biochemical processes specific to bacteria and archaea will be presented that contribute to the widespread occurrence of prokaryotes. Applied aspects of microbial biochemistry will be pointed out as well as research fields of current scientific interest. Emphasis is on concepts of energy generation and assimilation.

List of topics:
Microbial Biochemistry and origin of life
Methanogenesis and methylotrophy
Anaerobic oxidation of methane
Microbial autotrophy
Complex: (Ligno-)Cellulose and in demand for bioenergy
Challenging: Aromatics and hydrocarbons
Living on a diet and the anaplerotic provocation
20 amino acids: the making of
Extending the genetic code
The 21st and 22nd amino acid
Some exotic biochemistry: nucleotides, cofactors
Ancient biochemistry? Iron-sulfur clusters, polymers
Secondary metabolites: playground of evolution
LiteratureWill be provided during the course.
  •  Page  1  of  1