Search result: Catalogue data in Autumn Semester 2021

Biology Master Information
Elective Major Subject Areas
Elective Major: Ecology and Evolution
Compulsory Concept Courses
NumberTitleTypeECTSHoursLecturers
701-2413-00LEvolutionary GeneticsO6 credits4VT. Städler, A. Widmer, S. Fior, M. Fischer, J. Stapley
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.
701-0328-00LAdvanced Ecological Processes Restricted registration - show details
For students of the following study programmes only:
Biology Master
Teaching certificate Biology
Environmental Sciences Master
UZH MNF Biology
UZH MNF Geography /Earth Sciences
O4 credits2VJ. Hille Ris Lambers
AbstractThis course presents the theoretical and empirical approaches used to understand the ecological processes structuring communities. Central problems in community ecology including the dynamics of species interactions, the influence of spatial structure, the controls over species invasions, and community responses to environmental change will be explored from basic and applied perspectives.
ObjectiveStudents will understand how ecological processes operate in natural communities. They will appreciate how mathematical theory, field experimentation, and observational studies combine to generate a predictive science of ecological processes, and how this predictive science informs conservation and management decisions.

Upon completing the course, students will be able to:

Understand the factors determining the outcome of species interactions in communities, and how this information informs management.

Apply theoretical knowledge on species interactions to predict the potential outcomes of novel species introductions.

Understanding the role of spatial structure in mediating population dynamics and persistence, species interactions, and patterns of species diversity.

Use population and community models to predict the stability of interactions between predators and prey and between different competitors.

Understand the conceptual basis of predictions concerning how ecological communities will respond to climate change.

Discuss the types of conceptual advances ecology as a science can realistically achieve, and how these relate to the applications of the discipline.
ContentLectures supplemented with readings from the primary literature and occasional computer exercises will focus on understanding central processes in community ecology. Topics will include demographic and spatial structure, consumer resource interactions, food webs, competition, mutualism, invasion, the maintenance of species diversity, and species effects on ecosystem processes. Each of these more conceptual topics will be discussed in concert with their applications to the conservation and management of species and communities in a changing world.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesfostered
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingfostered
Media and Digital Technologiesfostered
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityfostered
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsfostered
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
Elective Compulsory Master Courses
NumberTitleTypeECTSHoursLecturers
751-4801-00LSystem-Oriented Management of Herbivore Insects
Does not take place this semester.
W2 credits2Gto be announced
AbstractThe focus is on the potential to assess strategies and tactics of pest management, in view of the demands from the economy, environment and society. Significant management measures will be explained using practical examples, such as surveillance and forecasting, resistance management, biological control as well as the use of plant protection products, incl. regulatory aspects and ecotoxicology.
ObjectiveThe students gain a good understanding of fundamental aspects of pest management in agroecosystems. They will be able to assess options for action in view of requirements from the economy, environment and society. Further, they will learn to elaborate on current issues in pest management, and to critically evaluate case studies.
701-1409-00LResearch Seminar: Ecological Genetics
Minimum number of participants is 5.
W2 credits1SS. Fior
AbstractIn this research seminar we will critically discuss recent publications on current topics in Ecological Genetics.
ObjectiveIt is our aim that participants gain insight into current research topics and approaches in Ecological Genetics and learn to critically assess and appreciate scientific publications in this field.
Lecture notesnone
Literaturewill be distributed
Prerequisites / NoticeActive and regular participation in the discussions, together with the presentation of a scientific paper are required to successfully pass this course.
It is strongly recommended that participants have in advance successfully participated in the course Evolutionary Genetics (701-2413-00) or Ecological Genetics (701-1413-01).
751-5121-00LInsect Ecology Restricted registration - show details
The number of participants is limited to 30.
W2 credits2VC. De Moraes, M. Mescher, N. Stanczyk
AbstractThis is an introductory class on insect ecology. During the course you will learn about insect interactions with, and adaptations to, their environment and other organisms, and the importance of insect roles in our ecosystems. This course includes lectures, small group discussions and outside readings.
ObjectiveThe aim of the course is to gain an understanding of how insects have specialised and adapted to occupy diverse environmental niches and become vital to ecosystem processes. Important topics include: insect-plant interactions, chemical ecology, predator-prey interactions, vectors of disease, social insects, mutual and parasitic interactions and examining insect ecology in an evolutionary context.
Lecture notesProvided to students through Moodle
LiteratureSelected required readings (peer reviewed literature). 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, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
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, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.
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 RegressionW5 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 "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.
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Techniques and Technologiesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Decision-makingassessed
Media and Digital Technologiesassessed
Problem-solvingassessed
Project Managementfostered
Social CompetenciesCommunicationassessed
Cooperation and Teamworkfostered
Customer Orientationfostered
Leadership and Responsibilityfostered
Self-presentation and Social Influence fostered
Sensitivity to Diversityfostered
Negotiationfostered
Personal CompetenciesAdaptability and Flexibilityassessed
Creative Thinkingassessed
Critical Thinkingassessed
Integrity and Work Ethicsassessed
Self-awareness and Self-reflection fostered
Self-direction and Self-management fostered
701-0301-00LApplied Systems Ecology Restricted registration - show details
Number of participants limited to 35.
Waiting list will be deleted October 3rd, 2021.
W3 credits2VA. Gessler, C. Grossiord
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) Restricted registration - show details W1.5 credits1GM. Mächler
AbstractThe course provides the first part an introduction to the statistical software R (Link) 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 and graphics.
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: Link

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. Link
Prerequisites / NoticeThe course resources will be provided via the Moodle web learning platform.
As from FS 2019, subscribing via Mystudies should *automatically* make you
a student participant of the Moodle course of this lecture,
which is at

Link
401-6217-00LUsing R for Data Analysis and Graphics (Part II) Restricted registration - show details W1.5 credits1GM. Mächler
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, graphics and simple programming
ContentThe course provides the second part of an introduction to the statistical software R (Link) 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: Link
Lecture notesAn Introduction to R. Link
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.
As from FS 2019, subscribing via Mystudies should *automatically* make you
a student participant of the Moodle course of this lecture,
which is at

Link
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 The nature of plant diseases, symbiosis, parasites, mutualism, biotrophs and necrotrophs, disease cycles and pathogen life cycles.

Week 2 Nematode attack strategies and types of damage. Viral pathogens, classification, reproduction and transmission, attack strategies and types of damage. Examples TMV, BYDV. Bacterial pathogens and phytoplasmas, classification, reproduction and transmission.

Week 3 Bacterial attack strategies and symptoms. Example bacterial diseases: fire blight, Agrobacterium crown gall, soft rots. Fungal and oomycete pathogens, classification, growth and reproduction, sexual and asexual spores, transmission.

Week 4 Fungal and oomycete life cycles, disease cycles, infection processes, colonization, phytotoxins and mycotoxins. Attack strategies of fungal necrotrophs and biotrophs. Symptoms and signs of fungal infection. Example fungal diseases: potato late blight.

Week 5 Example fungal diseases: wheat stem rust, grape powdery mildew, wheat septoria tritici blotch. Plant defense mechanisms, host range and non-host resistance. Passive structural and chemical defenses, preformed chemical defenses. Active structural defense, histological and cellular (papillae).

Week 6 Active chemical defense, hypersensitive response, pathogenesis-related (PR) proteins, phytoalexins and disease resistance. Pisatin and pisatin demethylase. Local and systemic acquired resistance (LAR, SAR), induced systemic resistance (ISR), signal molecules, defense activators (Bion). Pathogen effects on food quality. Positive and negative transformations.

Week 7 Negative pathogen impacts on crop yield and quality. Pathogen effects on food safety. Mycotoxins in the food chain. Aflatoxin, patulin safety assessment and action thresholds. Epidemiology: historical epidemics.

Week 8 Epidemiology: Disease pyramid, environmental effects on epidemic development, plant effects on development of epidemics, including resistance, physiology, density, uniformity.

Week 9 Disease assessment: incidence and severity measures, keys, diagrams, scales, measurement errors. Correlations between incidence and severity. Molecular detection and diagnosis of pathogens. Host indexing, serology, monoclonal and polyclonal antibodies, ELISA.

Week 10 Molecular detection and diagnosis of pathogens: PCR, rDNA and loop-mediated isothermal amplification. Strategies for minimizing disease risks: calculating disease thresholds, disease forecasting systems.

Week 11 Strategies for minimizing disease risks: lowering epidemic risk, ecological risk assessment, natural and synthetic pesticides. Disease control strategies: economic thresholds, overview of control strategies.

Week 12 Physical control methods. Cultural control methods: avoidance, tillage practices, crop sanitation.

Week 13 Cultural control methods: fertilizers, crop rotations.

Week 14 Open lecture.
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 BiologyW6 credits3G + 2AT. Vaughan
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 this data 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 for direct alignment analysis using approaches such as BLAST and GWAS. 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. Lastly, we introduce the field of phylodynamics, the aim of which is to understand and quantify 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 notesLecture slides will be available on moodle.
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. Programming in R will be required for the project work (compulsory continuous performance assessments). We provide an R tutorial and help sessions during the first two weeks of class to learn the required skills. However, in case you do not have any previous experience with R, we strongly recommend to get familiar with R prior to the semester start. For the D-BSSE students, we highly recommend the voluntary course „Introduction to Programming“, which takes place at D-BSSE from Wednesday, September 12 to Friday, September 14, i.e. BEFORE the official semester starting date Link
For the Zurich-based students without R experience, we recommend the R course Link, or working through the script provided as part of this R course.
701-1471-00LEcological Parasitology Restricted registration - show details
Number of participants limited to 20.
A minimum of 6 students is required that the course will take place.

Waiting list will be deleted on October 1st, 2021.
W3 credits1V + 1PJ. Jokela, C. Vorburger
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 invertebrates.
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. Ecology and evolution of parasitoids and their applications in biocontrol
5. Human macroparasites (schistosomiasis, malaria).

Practical exercises:
1. Examination of parasites in molluscs (identification and examination of host exploitation strategies).
2. Examination of parasites in amphipods (identification and examination of effects on hosts).
3. Examination of parasitoids of aphids.
Prerequisites / NoticeThe three practicals will take place at the 05.10.2021, the 19.10.2021 and the 09.11.2021 at Eawag Dübendorf from 08:15 - 12:00. Note that each practical takes 2 hours longer than the weekly lecture.
701-1427-00LExperimental Evolution Restricted registration - show details
Does not take place this semester.
Semester change.
This lecture will be offered in Spring Semester 2022 for the next time.
W4 credits2SG. Velicer, A. Hall
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 Evolutionary Analysis (or equivalent).
701-1703-00LEvolutionary Medicine for Infectious Diseases Restricted registration - show details
Number of participants limited to 35.

Waiting list will be deleted October 3rd, 2021.
W3 credits2GA. Hall
AbstractThis course explores infectious disease from both the host and pathogen perspective. Through short lectures, reading and active discussion, students will identify areas where evolutionary thinking can improve our understanding of infectious diseases and, ultimately, our ability to treat them effectively.
ObjectiveStudents will learn to (i) identify evolutionary explanations for the origins and characteristics of infectious diseases in a range of organisms and (ii) evaluate ways of integrating evolutionary thinking into improved strategies for treating infections of humans and animals. This will incorporate principles that apply across any host-pathogen interaction, as well as system-specific mechanistic information, with particular emphasis on bacteria and viruses.
ContentWe will cover several topics where evolutionary thinking is relevant to understanding or treating infectious diseases. This includes: (i) determinants of pathogen host range and virulence, (ii) dynamics of host-parasite coevolution, (iii) pathogen adaptation to evade or suppress immune responses, (iv) antimicrobial resistance, (v) evolution-proof medicine. For each topic there will be a short (< 20 minutes) introductory lecture, before students independently research the primary literature and develop discussion points and questions, followed by interactive discussion in class.
LiteratureThe focus is on primary literature, but for some parts the following text books provide good background information:

Schmid Hempel 2011 Evolutionary Parasitology
Stearns & Medzhitov 2016 Evolutionary Medicine
Prerequisites / NoticeA basic understanding of evolutionary biology, microbiology or parasitology will be advantageous but is not essential.
636-0009-00LEvolutionary DynamicsW6 credits2V + 1U + 2AN. Beerenwinkel
AbstractEvolutionary dynamics is concerned with the mathematical principles according to which life has evolved. This course offers an introduction to mathematical modeling of evolution, including deterministic and stochastic models, with an emphasis on tumor evolution.
ObjectiveThe goal of this course is to understand and to appreciate mathematical models and computational methods that provide insight into the evolutionary process in general and tumor evolution in particular. Students should analyze and evaluate models and their application critically and be able to design new models.
ContentEvolution is the one theory that encompasses all of biology. It provides a single, unifying concept to understand the living systems that we observe today. We will introduce several types of mathematical models of evolution to describe gene frequency changes over time in the context of different biological systems, focusing on asexual populations. Viruses and cancer cells provide the most prominent examples of such systems and they are at the same time of great biomedical interest. The course will cover some classical mathematical population genetics and population dynamics, and also introduce several new approaches. This is reflected in a diverse set of mathematical concepts which make their appearance throughout the course, all of which are introduced from scratch. Topics covered include the quasispecies equation, evolution of HIV, evolutionary game theory, evolutionary stability, evolutionary graph theory, tumor evolution, stochastic tunneling, genetic progression of cancer, diffusion theory, fitness landscapes, branching processes, and evolutionary escape.
Lecture notesNo.
Literature- Evolutionary Dynamics. Martin A. Nowak. The Belknap Press of Harvard University Press, 2006.
- Evolutionary Theory: Mathematical and Conceptual Foundations. Sean H. Rice. Sinauer Associates, Inc., 2004.
Prerequisites / NoticePrerequisites: Basic mathematics (linear algebra, calculus, probability)
CompetenciesCompetencies
Subject-specific CompetenciesConcepts and Theoriesassessed
Method-specific CompetenciesAnalytical Competenciesassessed
Problem-solvingassessed
Social CompetenciesCommunicationfostered
Cooperation and Teamworkfostered
Personal CompetenciesCritical Thinkingassessed
Self-direction and Self-management fostered
Elective Concept Courses
NumberTitleTypeECTSHoursLecturers
551-0313-00LMicrobiology (Part I)W3 credits2VW.‑D. Hardt, L. Eberl, 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 Genetics
Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module BIO348 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link
W6 credits4VY. Barral, D. Bopp, A. Hajnal, 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.
551-1299-00LIntroduction to Bioinformatics Restricted registration - show details W6 credits4GS. Sunagawa, M. Gstaiger, A. Kahles, G. Rätsch, B. Snijder, E. Vayena, C. von Mering, N. Zamboni
AbstractThis course introduces principle concepts, the state-of-the-art and methods used in some major fields of Bioinformatics. Topics include: genomics, metagenomics, network bioinformatics, and imaging. Lectures are accompanied by practical exercises that involve the use of common bioinformatic methods and basic programming.
ObjectiveThe course will provide students with theoretical background in the area of genomics, metagenomics, network bioinformatics and imaging. In addition, students will acquire basic skills in applying modern methods that are used in these sub-disciplines of Bioinformatics. Students will be able to access and analyse DNA sequence information, construct and interpret networks that emerge though interactions of e.g. genes/proteins, and extract information based on computer-assisted image data analysis. Students will also be able to assess the ethical implications of access to and generation of new and large amounts of information as they relate to the identifiability of a person and the ownership of data.
ContentEthics:
Case studies to learn about applying ethical principles in human genomics research

Genomics:
Genetic variant calling
Analysis and critical evaluation of genome wide association studies

Metagenomics:
Reconstruction of microbial genomes
Microbial community compositional analysis
Quantitative metagenomics

Network bioinformatics:
Inference of molecular networks
Use of networks for interpretation of (gen)omics data

Imaging:
High throughput single cell imaging
Image segmentation
Automatic analysis of drug effects on single cell suspension (chemotyping)
Prerequisites / NoticeCourse participants have already acquired basic programming skills in Python and R.

Students will bring and work on their own laptop computers, preferentially running the latest versions of Windows or MacOSX.
Elective Major: Microbiology and Immunology
Compulsory Concept Courses
NumberTitleTypeECTSHoursLecturers
551-0313-00LMicrobiology (Part I)O3 credits2VW.‑D. Hardt, L. Eberl, 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.
  •  Page  1  of  9 Next page Last page     All