Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Search result: Catalogue data in Autumn Semester 2016

Biology Master Information
Elective Major Subject Areas
Elective Major: Ecology and Evolution
Compulsory Concept Courses
NumberTitleTypeECTSHoursLecturers
701-2413-00LEvolutionary GeneticsO6 credits4VT. Städler, A. Widmer, P. C. Brunner, M. C. Fischer
AbstractThe concept course 'Evolutionary Genetics' consists of two lectures that jointly provide an introduction to the fields of population and quantitative genetics (emphasis on basic concepts) and ecological genetics (more emphasis on evolutionary and ecological processes of adaptation and speciation).
ObjectiveThe aim of the course is to provide students with a solid introduction to the fields of population genetics, quantitative genetics, and ecological genetics. The concepts and research methods developed in these fields have undergone profound transformations; they are of fundamental importance in our understanding of evolutionary processes, both past and present. Students should gain an appreciation for the concepts, methods and explanatory power of evolutionary genetics.
ContentPopulation genetics - Types and sources of genetic variation; randomly mating populations and the Hardy-Weinberg equilibrium; effects of inbreeding; natural selection; random genetic drift and effective population size; gene flow and hierarchical population structure; molecular population genetics: neutral theory of molecular evolution and basics of coalescent theory.
Quantitative genetics - Continuous variation; measurement of quant. characters; genes, environments and their interactions; measuring their influence; response to selection; inbreeding and crossbreeding, effects on fitness; Fisher's fundamental theorem.
Ecological Genetics - Concepts and methods for the study of genetic variation and its role in adaptation, reproductive isolation, hybridization and speciation
Lecture notesHandouts
LiteratureHamilton, M.B. 2009. Population Genetics. Wiley-Blackwell, Chichester, U.K.
Prerequisites / NoticeThere will be 5 optional extra sessions for the population genetics part (following lectures 2-6) for computer simulations, designed to help understand the course material.
701-0323-00LPlant EcologyO3 credits2VS. Güsewell, J. Levine
AbstractThis class focuses on ecological processes involved with plant life, mechanisms of plant adaptation, plant-animal and plant-soil interactions, plant strategies and implications for the structure and function of plant communities. The discussion of original research examples familiarises students with research questions and methods; they learn to evaluate results and interpretations.
ObjectiveStudents will be able to:
- propose methods to study ecological processes involved with plant life, and how these processes depend on internal and external factors;
- analyse benefits and costs of plant adaptations;
- explain plant strategies with relevant traits and trade-offs;
- explain and predict the assembly of plant communities;
- explain implications of plant strategies for animals, microbes and ecosystem functions;
- evaluate studies in plant ecology regarding research questions, assumptions, methods, as well as the reliability and relevance of results.
ContentPlants represent the matrix of natural communities. The structure and dynamics of plant populations drives the function of ecosystems. This course presents essential processes and plant traits involved with plant life. We focus on research questions that have been of special interest to plant ecologists as well as current topical questions. We use original research examples to discuss how ecological questions are studied and how results are interpreted.
- Growth: what determines the production of a plant?
- Nutrients: consumption or recycling: opposite strategies and feedbacks on soils;
- Clonality: collaboration and division of labour in plants;
- Plasticity: benefits and costs of plant intelligence;
- Flowering and pollination: how expensive is sex?
- Seed types, dispersal, seed banks and germination: strategies and trade-offs in the persistence of plant populations;
- Development and structure of plant populations;
- Stress, disturbance and competition as drivers of different plant strategies;
- Herbivory: plant-animal feedbacks and functioning of grazing ecosystems
- Fire: impacts on plants, vegetation and ecosystems.
- Plant functional types and rules in the assembly of plant communities.
Lecture notesHandouts and further reading will be available electronically at the beginning of the semester.
Prerequisites / NoticePrerequisites
- General knowledge of plant biology
- Basic knowledge of plant sytematics
- General ecological concepts
Elective Compulsory Master Courses
NumberTitleTypeECTSHoursLecturers
751-4801-00LSystem-Oriented Management of Herbivore Insects IW2 credits2GD. Mazzi
AbstractThe focus is on the potential to assess strategies and tactics of pest management, taking into account the demands from the economy, the environment and the society. Significant agricultural approaches will be explained using practical examples, including prevention using natural resources, surveillance and forecasting, resistance management, as well as product registration, incl. ecotoxicology.
ObjectiveThe students gain a good understanding of fundamental aspects of pest management in agroecosystems. They will have the ability to assess options for action in view of requirements from the economy, the ecology and the society. Further, they will learn to perform searches on relevant issues in pest management, and to critically evaluate case studies.
701-1409-00LResearch Seminar: Ecological Genetics Information
Minimum number of participants is 4.
W2 credits1SA. Widmer, S. Fior
AbstractIn this research seminar we will critically discuss current topics in Ecological Genetics using publications from the leading scientific journals in this field.
ObjectiveIt is our aim that participants gain insight into the current research topics and knowledge available in Ecological Genetics and learn to critically assess and appreciate scientific publications in this field.
Lecture notesnone
Literaturewill be distributed
Prerequisites / NoticeActive participation in the discussions is a prerequisite for this course.
551-1703-00LEcology of Anthropogenic HabitatsW2 credits1VD. Ramseier
AbstractThe focus will be on agro-ecology and ecology of urban habitats. Both experience frequent disturbances, specific chemical influences, and extreme climatic conditions. Additionally, in urban habitats edaphic conditions are difficult as well. Turnover of species diversity and composition are higher, both locally and temporary, compared to natural conditions at comparable sites.
ObjectiveKnowledge of agro-ecosystems and urban ecosystems; their origin, ecosystem services, mechanisms and importance for the maintenance of biodiversity.
701-1441-00LAlpine Ecology and Environments Information W2 credits2GS. Dietz, D. Ramseier
AbstractThe online course ALPECOLe provides a global overview of the complex ecosystems of mountain regions, and of their great diversity of habitats and organisms. The course is interdisciplinary and the various approaches are designed to help understand the past, present and future of mountain ecosystems.
ObjectiveKnowledge of alpine environments worldwide and their ecology
ContentThe online course is subdivided into
- 5 lessons on abiotic factors: geology, soils and their forming processes, climate, and disturbance factors
- 12 lessons on plants: diversity, patterns and processes, treelines, water & nutrients, carbon cycle, atmospheric influences, sexual and clonal reproduction, and one specific lesson on aquatic environments
- 5 lessons on animals: habitats and adaptations, origin of species, food ecology and impact of domestic livestock
- 3 lessons on landscape evolution: quarternary paleoenvironments, methods like radiocarbon dating, pollen records, dendrochronology, stable isotopes, and historical data
- 1 lesson on global change

Students can also follow a virtual walk through alpine areas where context-based information on alpine environments can be accessed. Moreover, all mayor alpine areas of the world can be selected on a map and then informative pictures of those landscapes and faunistic and floristic inhabitants will be shown.
Online exercises and tests allow to test the learned matter.
Prerequisites / NoticeOnline course and seminar
Students prepare for the seminar by working through particular lessons. Each student has to present some special aspect of one lesson. The seminar contribution is part of the performance assessment.
Course language is English
751-5121-00LInsect EcologyW2 credits2VR. R. Kariyat Ramachandran, C. De Moraes, M. Mescher
AbstractThis is an introductory course in insect ecology. Students will learn about the ways in which insects interact with and adapt to their abiotic & biotic environments and their roles in diverse ecosystems. The course will entail lectures, outside readings, and critical analysis of contemporary literature.
ObjectiveStudents completing this course should become familiar with the application of ecological principles to the study of insects, as well as major areas of inquiry in this field. Highlighted topics will include insect behavior, chemical and sensory ecology, physiological responses to biotic and abiotic stressors, plant-insect interactions, community and food-web dynamics, and disease ecology. The course will emphasize insect evolution and adaptation in the context of specific interactions with other organisms and the abiotic environment. Examples from the literature incorporated into lectures will highlight the methods used to study insect ecology.
Lecture notesProvided to students through ILIAS
LiteratureSelected required readings (peer reviewed literature, selected book chapters). Optional recommended readings with additional information.
401-0625-01LApplied Analysis of Variance and Experimental Design Information W5 credits2V + 1UL. Meier
AbstractPrinciples of experimental design. One-way analysis of variance. Multi-factor experiments and analysis of variance. Block designs. Latin square designs. Split-plot and strip-plot designs. Random effects and mixed effects models. Full factorials and fractional designs.
ObjectiveParticipants will be able to plan and analyze efficient experiments in the fields of natural sciences. They will gain practical experience by using the software R.
ContentPrinciples of experimental design. One-way analysis of variance. Multi-factor experiments and analysis of variance. Block designs. Latin square designs. Split-plot and strip-plot designs. Random effects and mixed effects models. Full factorials and fractional designs.
LiteratureG. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000.
Prerequisites / NoticeThe exercises, but also the classes will be based on procedures from the freely available, open-source statistical software R, for which an introduction will be held.
401-0649-00LApplied Statistical Regression Information W5 credits2V + 1UM. Dettling
AbstractThis 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.
ObjectiveThe students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling.
ContentThe 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 notesA script will be available.
LiteratureFaraway (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 / NoticeThe 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 "Regression" 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.
701-0301-00LApplied Systems EcologyW3 credits2VD. Schröter, A. Gessler
AbstractThis course provides the ecological systems` knowledge needed to question applied solutions to current environmental issues. Our central aim is to balance participants' respect for complexity with a sense of possibility by providing examples from the vast solution space offered by ecological systems, such as e.g. green infrastructure to manage water.
ObjectiveAt the end of the course...
...you know how to structure your inquiry and how to proceed the analysis when faced with a complex environmental issue. You can formulate the relevant questions, find answers (supported by discussions, input from the lecturers and the literature), and you are able to present your conclusions clearly and cautiously.
...you understand the complexity of interactions and structures in ecosystems. You know how ecosystem processes, functions and services interact and feed back across multiple spatio-temporal scales (in general, plus in depth case examples).
...you understand that biodiversity and the interaction between organisms are an integral part of ecosystems. You are aware that the link between biodiversity and process/function/service is rarely fully understood. You know how to honestly deal with this lack of understanding and can nevertheless find, critically analyse and communicate solutions.
...you understand the importance of ecosystem services for society.
...you have an overview of the methods of ecosystem research and have a deeper insight into some of them, e.g. ecosystem observation, manipulation and modelling.
...you have reflected on ecology as a young discipline at the heart of significant applied questions.
ContentThis course provides the ecological systems' knowledge needed to question applied sustainability solutions. We will critically assess the complexity of current environmental issues, illustrating basic ecological concepts and principles. Our central aim is to balance participants' respect for complexity with a sense of possibility by providing examples from the vast solution space offered by ecological systems, such as e.g. green infrastructure to manage water.

The course is structured around four larger topical areas: (1) Integrated Water Management -- Green infrastructure (land management options) as an alternative to engineered solutions (e.g. large reservoirs) in flood and drought management; (2) Fire dynamics, the water cycle and biodiversity -- The surprising dynamics of species life cycles and populations in arid landscapes; (3) Rewilding, e.g. re-introducing apex predators (e.g. wolves), or large ungulates (e.g. bisons) in protected areas -- A nature conservation trend with counterintuitive effects; (4) Coupling of aquatic and terrestrial systems: carbon, nitrogen and phosphorus transfers of global importance on landscape scale.
Lecture notesCase descriptions, commented glossary and a list of literature and further resources per case.
LiteratureIt is not essential to borrow/buy the following books. We will continuously provide excerpts and other literature during the course.

Agren GI and Andersson FO (2012) Principles of Terrestrial Ecosystem Ecology, Cambridge University Press.

Chapin et al. (2011), Principles of Terrestrial Ecosystem Ecology, Springer.

Schulze et al. (2005) Plant Ecology; Springer.
Prerequisites / NoticeThe course combines elements of a classic lecture, group discussions and problem based learning. It is helpful, but not essential to be familiar with the "seven stages" method (see e.g. course 701-0352-00L "Analysis and Assessment of Environmental Sustainability" by Christian Pohl et al.).
401-6215-00LUsing R for Data Analysis and Graphics (Part I) Information W1 credit1GA. Drewek, A. J. Papritz
AbstractThe course provides the first part an introduction to the statistical software R for scientists. Topics covered are data generation and selection, graphical and basic statistical functions, creating simple functions, basic types of objects.
ObjectiveThe students will be able to use the software R for simple data analysis.
ContentThe 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. 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 notesAn Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf
Prerequisites / NoticeThe course resources will be provided via the Moodle web learning platform
Please login (with your ETH (or other University) username+password) at
https://moodle-app2.let.ethz.ch/enrol/users.php?id=1145
Choose the course "Using R for Data Analysis and Graphics" and follow the instructions for registration.
401-6217-00LUsing R for Data Analysis and Graphics (Part II) Information W1 credit1GA. Drewek, A. J. Papritz
AbstractThe course provides the second part an introduction to the statistical software R for scientists. Topics are data generation and selection, graphical functions, important statistical functions, types of objects, models, programming and writing functions.
Note: This part builds on "Using R... (Part I)", but can be taken independently if the basics of R are already known.
ObjectiveThe students will be able to use the software R efficiently for data analysis.
ContentThe course provides the second 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 II of the course builds on part I and covers the following additional topics:
- Elements of the R language: control structures (if, else, loops), lists, overview of R objects, attributes of R objects;
- More on R functions;
- Applying functions to elements of vectors, matrices and lists;
- Object oriented programming with R: classes and methods;
- Tayloring R: options
- Extending basic R: packages

The course focuses on practical work at the computer. We will make use of the graphical user interface RStudio: www.rstudio.org
Lecture notesAn Introduction to R. http://stat.ethz.ch/CRAN/doc/contrib/Lam-IntroductionToR_LHL.pdf
Prerequisites / NoticeBasic knowledge of R equivalent to "Using R .. (part 1)" ( = 401-6215-00L ) is a prerequisite for this course.

The course resources will be provided via the Moodle web learning platform
Please login (with your ETH (or other University) username+password) at
https://moodle-app2.let.ethz.ch/enrol/users.php?id=1145
Choose the course "Using R for Data Analysis and Graphics" and follow the instructions for registration.
751-4504-00LPlant Pathology IW2 credits2GB. McDonald
AbstractPlant Pathology I will focus on pathogen-plant interactions, epidemiology, disease assessment, and disease development in agroecosystems. Themes will include: 1) how pathogens attack plants and; 2) how plants defend themselves against pathogens; 3) factors driving the development of epidemics in agroecosystems.
ObjectiveStudents will understand: 1) how pathogens attack plants and; 2) how plants defend themselves against pathogens; 3) factors driving the development of epidemics in agroecosystems as a basis for implementing disease management strategies in agroecosystems.
ContentCourse description: Plant Pathology I will focus on pathogen-plant interactions, epidemiology, disease assessment, and disease development in agroecosystems. Themes will include: 1) how pathogens attack plants and; 2) how plants defend themselves against pathogens; 3) factors driving the development of epidemics in agroecosystems. Topics under the first theme will include pathogen life cycles, disease cycles, and an overview of plant pathogenic nematodes, viruses, bacteria, and fungi. Topics under the second theme will include plant defense strategies, host range, passive and active defenses, and chemical and structural defenses. Topics under the third theme will include the disease triangle and cultural control strategies.

Lecture Topics and Tentative Schedule

Week 1 No Lecture: First day of autumn semester

Week 2 The nature of plant diseases, symbiosis, parasites, mutualism, biotrophs and necrotrophs, disease cycles and pathogen life cycles. Nematode attack strategies and types of damage.

Week 3 Viral pathogens, classification, reproduction and transmission, attack strategies and types of damage. Examples TMV, BYDV, plum pox virus. Bacterial pathogens and phytoplasmas, classification, reproduction and transmission. Bacterial attack strategies and symptoms. Example bacterial diseases: fire blight, Agrobacterium crown gall, soft rots.

Week 4 Fungal pathogens, classification, growth and reproduction, sexual and asexual spores, transmission. Fungal life cycles, disease cycles, infection processes, colonization, phytotoxins and mycotoxins. Attack strategies of fungal necrotrophs and biotrophs.

Week 5 Symptoms and signs of fungal infection. Example fungal diseases: potato late blight, wheat stem rust, grape powdery mildew, wheat Septoria leaf blotch.

Week 6 Plant defense mechanisms, host range and non-host resistance. Passive structural and chemical defenses, preformed chemical defenses. Active structural defense, papillae, active chemical defense, hypersensitive response, pathogenesis-related (PR) proteins, phytoalexins and disease resistance.

Week 7 Pisatin and pisatin demethylase. Local and systemic acquired resistance, signal molecules.

Week 8 Pathogen effects on food quality and safety.

Week 9 Epidemiology: historical epidemics, disease pyramid, environmental effects on epidemic development. Plant effects on development of epidemics, including resistance, physiology, density, uniformity.

Week 10 Disease assessment: incidence and severity measures, keys, diagrams, scales, measurement errors. Correlations between incidence and severity.

Week 11 Molecular detection and diagnosis of pathogens. Host indexing, serology, monoclonal and polyclonal antibodies. ELISA, PCR, rDNA and rep-PCR.

Week 12 Strategies for minimizing disease risks: principles of disease control and management.

Week 13 Disease control strategies: economic thresholds, physical control methods.

Week 14 Cultural control methods: avoidance, tillage practices, crop sanitation, fertilizers, crop rotation.
Lecture notesDetailed lecture notes (~160 pages) will be available for purchase at the cost of reproduction at the start of the semester.
636-0017-00LComputational Biology Information W4 credits3GT. Stadler, C. Magnus
AbstractThe aim of the course is to provide up-to-date knowledge on how we can study biological processes using genetic sequencing data. Computational algorithms extracting biological information from genetic sequence data are discussed, and statistical tools to understand this information in detail are introduced.
ObjectiveAttendees will learn which information is contained in genetic sequencing data and how to extract information from them using computational tools. The main concepts introduced are:
* stochastic models in molecular evolution
* phylogenetic & phylodynamic inference
* maximum likelihood and Bayesian statistics
Attendees will apply these concepts to a number of applications yielding biological insight into:
* epidemiology
* pathogen evolution
* macroevolution of species
ContentThe course consists of four parts. We first introduce modern genetic sequencing technology, and algorithms to obtain sequence alignments from the output of the sequencers. We then present methods to directly analyze this alignment (such as BLAST algorithm, GWAS approaches). Second, we introduce mechanisms and concepts of molecular evolution, i.e. we discuss how genetic sequences change over time. Third, we employ evolutionary concepts to infer ancestral relationships between organisms based on their genetic sequences, i.e. we discuss methods to infer genealogies and phylogenies. We finally introduce the field of phylodynamics. The aim of that field is to understand and quantify the population dynamic processes (such as transmission in epidemiology or speciation & extinction in macroevolution) based on a phylogeny. Throughout the class, the models and methods are illustrated on different datasets giving insight into the epidemiology and evolution of a range of infectious diseases (e.g. HIV, HCV, influenza, Ebola). Applications of the methods to the field of macroevolution provide insight into the evolution and ecology of different species clades. Students will be trained in the algorithms and their application both on paper and in silico as part of the exercises.
Lecture notesSlides of the lecture will be available online.
https://www.bsse.ethz.ch/cevo/education/cb-materials.html
LiteratureThe course is not based on any of the textbooks below, but they are excellent choices as accompanying material:
* Yang, Z. 2006. Computational Molecular Evolution.
* Felsenstein, J. 2004. Inferring Phylogenies.
* Semple, C. & Steel, M. 2003. Phylogenetics.
* Drummond, A. & Bouckaert, R. 2015. Bayesian evolutionary analysis with BEAST
Prerequisites / NoticeBasic knowledge in linear algebra, analysis, and statistics will be helpful. Some programming experience will be useful for the exercises, but is not required. Programming skills will not be tested in the examination.
701-1419-00LAnalysis of Ecological DataW2 credits2GS. Güsewell
AbstractThis class provides students with an overview of techniques for data analysis used in modern ecological research, as well as practical experience in running these analyses with R and interpreting the results. Topics include linear models, generalized linear models, mixed models, model selection and randomization methods.
ObjectiveStudents will be able to:
- describe the aims and principles of important techniques for the analysis of ecological data
- choose appropriate techniques for given problems and types of data
- evaluate assumptions and limitations
- implement the analyses in R
- represent the relevant results in graphs, tables and text
- interpret and evaluate the results in ecological terms
Content- Linear models for experimental and observational studies
- Model selection
- Introduction to likelihood inference and Bayesian statistics
- Analysis of counts and proportions (generalised linear models)
- Models for non-linear relationships
- Grouping and correlation structures (mixed models)
- Randomisation methods
Lecture notesLecture notes and additional reading will be available electronically a few days before the course
LiteratureSuggested books for additional reading (available electronically)
Zuur A, Ieno EN & Smith GM (2007) Analysing ecological data. Springer, Berlin.
Zuur A, Ieno EN, Walker NJ, Saveliev AA & Smith GM (2009) Mixed effects models and extensions in ecology with R. Springer, New York.
Faraway JJ (2006) Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models. Taylor & Francis.
Prerequisites / NoticeTime schedule
The course takes place over a period of nine days from Thursday 12.01 to Friday 20.01, with classes on 12, 13, 16, 17 and 18.01. and an exam in the morning of 20.01.

Prerequisites
- Basic statistical training (e.g. Mathematik IV in D-USYS): Data distributions, descriptive statistics, hypothesis testing, linear regression, analysis of variance
- Basic experience in data handling and data analysis in R

Individual preparation
Students without the required knowledge are asked to contact the lecturer before Christmas for support with individual preparation.
701-1471-00LEcological Parasitology Information Restricted registration - show details
Number of participants limited to 20.

Enrollment is limited to Master students of the study programme Environmental Sciences majoring Ecology and Evolution and to Master students of the study programme Biology majoring Ecology and Evolution (Elective Compulsory Master Courses), time of enrolment is decisive.
It is possible to enroll until September 12. The registration will only be effective once confirmed.
W3 credits1V + 1PO. E. Seppälä, H. Hartikainen, J. Jokela
AbstractCourse focuses on the ecology and evolution of macroparasites and their hosts. Through lectures and practical work, students learn about diversity and natural history of parasites, adaptations of parasites, ecology of host-parasite interactions, applied parasitology, and human macroparasites in the modern world.
Objective1. Identify common macroparasites in aquatic organisms.
2. Understand ecological and evolutionary processes in host-parasite interactions.
3. Conduct parasitological research.
ContentLectures:
1. Diversity and natural history of parasites (i.e. systematic groups and life-cycles).
2. Adaptations of parasites (e.g. evolution of life-cycles, host manipulation).
3. Ecology of host-parasite interactions (e.g. parasite communities, effects of environmental changes).
4. Applied parasitology (e.g. aquaculture and fisheries).
5. Human macroparasites (schistosomiasis, malaria).

Practical exercises:
1. Examination of parasites in fish (identification of species and description of parasite communities).
2. Examination of parasites in molluscs (identification and examination of host exploitation strategies).
3. Examination of parasites in amphipods (identification and examination of effects on hosts).
701-1427-00LExperimental EvolutionW4 credits2SG. Velicer, A. Hall, S. Wielgoss, Y.‑T. N. Yu
AbstractStudents will analyze experimental evolution literature covering a wide range of questions, species and types of analysis and will lead discussions of this literature. Students will develop a written project proposal for a novel evolution experiment (or a novel analysis of a published experiment) to address an unanswered question and will also deliver an oral presentation of the project proposal.
ObjectiveCourse objectives:
i) become familiar with a diverse sample of experimental evolution literature,
ii) gain understanding of the strengths and limitations of experimental evolution for addressing evolutionary questions relative to other forms of evolutionary analysis, and
iii) gain the ability to effectively design and analyze evolution experiments that address fundamental or applied questions in evolutionary biology.
ContentExperimental evolution is a powerful and increasingly prominent approach to investigating evolutionary processes. Students will analyze experimental evolution literature covering a diverse range of topics, species and types of analysis and will lead discussions of this literature. Students will develop a written project proposal for a novel evolution experiment (or a novel analysis of a published experiment) to address an unanswered question and will also deliver an oral presentation of the project proposal. Evaluation will be based on a combination of participation in and leadership of literature discussions, in-class exams, and oral and written presentations of the project proposal.
LiteraturePrimary research papers and review articles.
Prerequisites / Notice701-0245-00 Introduction to Evolutionary Biology (or equivalent).
Elective Concept Courses
NumberTitleTypeECTSHoursLecturers
551-1295-00LIntroduction to Bioinformatics: Concepts and Applications Information W6 credits4GW. Gruissem, K. Bärenfaller, A. Caflisch, G. Capitani, J. Fütterer, M. Robinson, A. Wagner
AbstractStorage, handling and analysis of large datasets have become essential in biological research. The course will introduce students to a number of applications of bioinformatics in biology. Freely accessible software tools and databases will be explained and explored in theory and praxis.
ObjectiveIntroduction to Bioinformatics I: Concepts and Applications (formerly Bioinformatics I) will provide students with the theoretical background of approaches to store and retrieve information from large databases. Concepts will be developed how DNA sequence information can be used to understand phylogentic relationships, how RNA sequence relates to structure, and how protein sequence information can be used for genome annotation and to predict protein folding and structure. Students will be introduced to quantitative methods for measuring gene expression and how this information can be used to model gene networks. Methods will be discussed to construct protein interaction maps and how this information can be used to simulate dynamic molecular networks.

In addition to the theoretical background, the students will develop hands-on experiences with the bioinformatics methods through guided exercises. The course provides students from different backgrounds with basic training in bioinformatics approaches that have impact on biological, chemical and physics experimentation. Bioinformatics approaches draw significant expertise from mathematics, statistics and computational science.

Although "Intoduction to Bioinformatics I" will focus on theory and praxis of bioinformatics approaches, the course provides an important foundation for the course "Introduction to Bioinformatics II: Fundamentals of computer science, modeling and algorithms" that will be offered in the following semester.
ContentBioinformatics I will cover the following topics:

From genes to databases and information
BLAST searches
Prediction of gene function and regulation
RNA structure prediction
Gene expression analysis using microarrays
Protein sequence and structure databases
WWW for bioinformatics
Protein sequence comparisons
Proteomics and de novo protein sequencing
Protein structure prediction
Cellular and protein interaction networks
Molecular dynamics simulation
551-0313-00LMicrobiology (Part I) Information W3 credits2VW.‑D. Hardt, L. Eberl, H.‑M. Fischer, J. Piel, M. Pilhofer
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
The lecture "Grundlagen der Biologie II: Mikrobiologie" is the basis for this advanced lecture.
551-0309-00LConcepts in Modern GeneticsW6 credits4VY. Barral, D. Bopp, A. Hajnal, M. Stoffel, O. Voinnet
AbstractConcepts of modern genetics and genomics, including principles of classical genetics; yeast genetics; gene mapping; forward and reverse genetics; structure and function of eukaryotic chromosomes; molecular mechanisms and regulation of transcription, replication, DNA-repair and recombination; analysis of developmental processes; epigenetics and RNA interference.
ObjectiveThis course focuses on the concepts of classical and modern genetics and genomics.
ContentThe topics include principles of classical genetics; yeast genetics; gene mapping; forward and reverse genetics; structure and function of eukaryotic chromosomes; molecular mechanisms and regulation of transcription, replication, DNA-repair and recombination; analysis of developmental processes; epigenetics and RNA interference.
Lecture notesScripts and additional material will be provided during the semester.
Prerequisites / NoticeThis course is a co-production of the University of Zurich and ETH Zurich, and will be taught in English. The course takes place on Monday afternoon at ETH Hoenggerberg, and on Tuesday morning at UZH Irchel.
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