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(1 ECTS), Prof. Nina Buchmann, Prof. Emmanuel Frossard, Prof. Johan Six, Dr. Roland Werner, Dr. Matthias Barthel, Dr. Charlotte Decock (ETH Zurich) and Prof. Ansgar Kahmen (University of Basel). Scientists at both field sites (DOK trial: Dr. Paul Mäder, Dr. Andreas Fliessbach (FiBl), Juliane Hirte (Agroscope); Hofstetten crane: Ansgar Kahmen)
Lectures: Introduction to stable isotopes, tracer vs. natural abundance applications, instrumentation. Overview lectures on stable carbon, nitrogen, oxygen and hydrogen isotope applications in agricultural and forest ecosystem sciences. Field visit: Students will get to know stable isotope applications in agricultural (DOK trial) and forest (Hofstetten crane site) ecosystems, interact with those who had carried out different stable isotope studies at the sites. Students know the basics about stable isotope applications to study plant and soil related research questions. Students are able to decide on tracer vs. natural abundance designs for a given research objective. Students understand the main mechanisms and processes imprinting on the stable isotope composition of the material of interest (e.g., plants, soils, gases).
The course offers an opportunity to Swiss-based students to apply their knowledge and challenge their preconceptions to novel socio-environmental situations. The course specifically encourages students to explore and evaluate alternative management approaches that seek to integrate local economic needs with conservation priorities. An understanding of changing human perspectives to conservation (and associated land management approaches) will be gained. Using this understanding students will consider future challenges to conservation and land management, and develop solutions to resolve them.
The course will allow students to learn about ecology, conservation and management issues in a unique landscape. Daily excursions will focus on specific important issues relating to conservation management in the area. Excursions will be led by local experts representing science, management and policy, each of whom will explore with the students the complexities of the chosen topics. Topics will encompass species, habitats and landscapes from economic, ecological and cultural perspectives across various spatial and temporal scales.
Students will be encouraged to explore selected topics in more detail, examples being (1) trade-offs between deer, that are important to the local economy, and the regeneration of Caledonian pine forests, (2) the implications of changing land use and land-tenure systems, (3) the management of tourism on sensitive upland habitats, (4) securing a balance between renewable energy generation (e.g. wind farms, forestry) and landscape beauty, (5) predicted effects of climate change on plant communities, and (6) the impact of invasive species on natural plant communities.
In the evenings, group presentations and discussions based on the accumulated knowledge will aim to develop feasible solutions to current conservation challenges.
3 ECTS (90 learning hours)
Every second year (last 2017), next dates are not available
Lecturer: Prof. Jaboury Ghazoul, ETH Zurich
(1 ECTS), Prof. Thomas Boller, University of Basel
The aim of this course is to present an introduction to and overview of theory and experimental approaches to investigate "innate immunity" in plants. Recent work has shown that innate immunity in plants and animals are based on similar basic principles. In particular, both plants and animals recognize so-called "pathogen-associated molecular patterns" (PAMPs). These PAMPs elicit a defense response including formation of reactive oxygen species and induction of a multitude of genes.
Light microscopy is a frequently used tool in plant sciences. Still, many are not aware of all the factors that are necessary for good quality, reproducible microscopy images. The aim of the course is to give the participants a practice-oriented introduction to the basics of light microscopy, including a short introduction to image processing. This 3-day course offers a basic introduction into light microscopy. During the mornings lectures will summarize the necessary theory and the afternoon session will concentrate on practical, hands-on exercises. The following subjects will be dealt with transmission microscopy (phase contrast, DIC), fluorescence microscopy (including confocal imaging), basics of image processing.
Individual Performance and Assessment: Active participation during the course and in the hands-on training is necessary.
1 ECTS (30 learning hours)
Every two years (last autumn 2021, next 2023)
Lecturer: Dr. Gábor Csúc and Nicolas Blanc, ETH Zurich,
(1 ECTS), Prof. Alex Widmer, ETH Institut für Integrative Biologie, Dr. Stefan Zoller and Dr. Jean-Claude Walser, Genetic Diversity Center, ETH Zurich
The goal of DNA barcoding is the identification of species through the analysis of nucleotide variation in short, standardized gene regions. These gene regions are typically amplified by PCR from samples of unknown origin and are then sequenced individually using standard Sanger sequencing technology. DNA metabarcoding is an extension that aims at identifying multiple species from a single, often complex and possibly degraded, environmental sample. A target gene region from all species represented in the sample is then amplified by PCR and sequenced using a high throughput nucleotide sequencing approach. DNA barcoding is widely used by ecologists and conservation biologists to identify species. Examples include the analysis of wood samples from logged trees or the validation of field identifications of vegetative plant parts. DNA metabarcoding is mainly used by ecologists and evolutionary biologists interested in biodiversity assessment, for example from water or soil samples, or the analysis of animal diet, gut bacteria composition and parasite diversity.
(1 ECTS), Prof. Beat Keller, University of Zurich
Genetic resistance is the most economical and environmentally friendly option for controlling plant diseases in agricultural ecosystems. Plant breeders have expended considerable effort to incorporate resistance genes into the major crops over the past 100 years. Pathogens have evolved to overcome many of these resistance genes, leading to a cycle of boom-and-bust with significant economic and societal consequences. This course will explore the molecular basis of disease resistance with an emphasis on agricultural crops. Topics will include: mechanisms of resistance; major gene resistance and quantitative resistance; genetic and biochemical models of gene-for-gene interactions; resistance gene structure and evolution; effector molecules in pathogens, boom-and-bust cycles and durable resistance; resistance gene deployment and management strategies; approaches for genetic engineering of resistance; identification and mapping of major resistance genes and quantitative (QTL) resistance; bioinformatics of plant pathogen genomes (“Pathogenomics”).
The fluxes that flow through the plant metabolic network sustain life and are directly linked to the agronomically important parameters of crop yield and composition. Flux is the only direct measure of metabolic activity, and so measurements of metabolic flux allow the definition of metabolic phenotypes that are closely related to biological function. An understanding of these phenotypes and the flux distributions that define them is therefore essential for analysis of the behavior and regulation of the plant metabolic network. This course provides a theoretical and practical introduction to the methods available for measuring, inferring or predicting fluxes and considers how this knowledge informs our understanding of the function of the plant metabolic network. The course will describe the methods used for the prediction and measurement of fluxes in the plant metabolic network. It will provide an assessment of the applicability of these methods and a discussion of the significance of the results that have been obtained. This will include an analysis of the contribution of these methods to our understanding of the network as well as a discussion of the relevance of the methods to plant metabolic engineering. The lectures will be complemented by computing sessions that will introduce some of the modelling software used to analyse fluxes, providing an opportunity to explore the complex (and often counter-intuitive) behavior of metabolic networks.
Individual Performance and Assessment: Participants will be assessed on the basis of their contribution to the practical exercises that are integral to the course.
1 ECTS (24 learning hours)
Biannually (last 2018)
Lecturer: Prof. R. George Ratcliffe, Dr Nicholas J. Kruger, Department of Plant Sciences, University of Oxford, UK
Molecular data provide rich information about the biological forces shaping biodiversity. Molecular phylogenies are now routinely used to test a variety of biological hypotheses, with applications ranging from medicine and epidemiology to agriculture and ecology. Natural selection is one of the major forces shaping the genomic diversity, often responsible for adaptations to new pathogens and environments. This course will provide an introduction to modelling the molecular evolution, phylogeny inference and statistical hypothesis testing in phylogenetics. These techniques became a must in most genomic analyses. Models of sequence substitution, Inferring phylogenies in a nutshell, Detecting positive selection at the protein coding level.
Individual Performance and Assessment: Project-based individual assignment, which should be submitted within 1 week after the course.
1 ECTS (30 learning hours)
Triannually (last 2019)
Lecturer: Dr. Maria Anisimova, ZHAW
(3 ECTS), Prof. Emmanuel Frossard, ETH Zurich
Radio-isotopes are extensively used at the soil/plant or ecosystem level to quantify the fluxes of elements (phosphorus (P), heavy metals, radionuclides) within a given system and to assess the importance of processes controlling these fluxes (e.g. exchange reactions between the soil solution and the soil solid phase, element turnover through the microbial biomass, organic matter mineralization etc.).
The course will first present the principles, the basic assumptions and the theoretical framework that underlay the work with radioisotopes. It will present how the introduction of an isotope into a system can be done so as to get information on the structure of the system (e.g. number and size of compartments). Secondly, case studies on isotopic dilution and tracer work will be presented for instance on the isotopic exchange kinetics method to determine nutrients or pollutants availability. The case studies will be adapted to the ongoing research of the group of plant nutrition and will thus give an insight into our current research. In addition, published studies will be analyzed and presented by the students. Finally, the advantages and disadvantages of work with radioisotopes will be analyzed and discussed critically.
Utilization of non-human biological material that comes from abroad is more than just a matter of competence in research techniques and methods. Scientists must be aware of legal and procedural requirements in order to correctly access biological material and to respect existing international and national regulations on plant genetic resources. Researchers need to be familiar with the Nagoya Protocol and terms such as Prior Informed Consent, Mutually Agreed Terms, Benefit-Sharing and Due Diligence in research. The overall goal of this course is to inform young scientists about the relevant international treaties and existing international and Swiss regulations that affect research projects with genetic resources and to illustrate which steps to undertake.
Training will focus on the a) Nagoya Protocol on Access to Genetic Resources and Benefit Sharing (ABS) and the Convention on Biological Diversity (CBD), b) International Treaty on Plant Genetic Resources for Food and Agriculture (IT FAO), and c) Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The course will provide solid knowledge on a) Correct and legitimate access to genetic resources and benefit-sharing for academic research,b) The Multilateral System of the plant treaty (ITPGRFA), c) Requirements for importing material under CITES in general, and specifically for plant genetic resources, and d) Swiss regulations, and available support and counseling services for scientists in Switzerland.
Individual Performance and Assessment: Participants are expected to submit a project description of their research project before the course starts.
1 ECTS (30 learning hours)
Biannually (last 2017)
Lecturer: Dr. Susette Biber-Klemm, SCNAT & University of Basel; Sylvia Martínez M.Sc., Univ. of Basel & Zurich-Basel Plant Science Center
Next-generation sequencing (NGS) technologies have revolutionized many fields in biology. The Functional Genomics Center Zurich (FGCZ) offers a four-day course with hands-on practicals. The aim is to help scientists interested in NGS technologies, particularly applied to RNA sequencing, to gain a better understanding of the techniques available and their applications. The practical consists of a library preparation starting from polyA enriched RNA, followed by a sequencing run on a bench top sequencer. An introduction to the analyses of the resulting data and some exercises will be offered too. The lectures cover existing and upcoming NGS technologies, their applications and the principles of downstream data analysis. By the end of the course participants should be able to make informed decisions about which technology and workflow to apply to solve specific research questions.
Course Program
Library Prep: PolyA RNA-seq library generation: principles and types
Sequencing: Detailed description of available sequencing technologies platforms, Hands-on laboratory work: preparing and performing sequencing runs
Data analysis: Run QC: Criteria for run performance and quality of data, Preprocessing of the raw data, Mapping the data to a reference, Mapping quality control for RNA-seq data, Transcripts expression quantification and tests for differential expression, Set-based analysis (e.g., pathways, GO-categories) IT and awareness of the data storage and its size
Individual Performance and Assessment: Attendance and active participation during all four days of the course (32 hours) plus completing an individual assignment of around 6 hours.
1 ECTS (38 learning hours)
Biannually (last 2018, next to be announced)
Lecturer: Dr. Lucy Poveda, Dr. Weihong Qi and others, Functional Genomics Center Zurich
(1 ECTS), Luc Henry, Syngenta Basel, Switzerland
Currently, there is a remarkable gap between public perception and understanding of world agriculture and its role in our society. This places enormous stress and tension not only on governments and agribusinesses, but also on individuals as consumers. This gap, unfortunately, is widening and future opinion leaders have a major role to play in filling this gap. The objective of this course therefore is to provide students with the opportunity to explore the topic of world agriculture (including production and consumption, the technologies used and being developed, the impact on the environment, the food security challenge, the carbon footprint of agriculture, the biofuels, etc), and to put in place a framework to understand and foresee the potential required changes over the next years. The purpose of the course, by its very nature, is not to provide a single, “correct” perspective about agriculture. Instead, it aims at making students aware of possible scenarios, the consequences of the different scenarios, and help them to shape their own vision of agriculture in 2020.
The three day interactive workshop is designed to train participants in topics and skills relating to the responsible planning, conduct, analysis and communication of research. During the first two days, participants will explore the principles and challenges of research integrity and reproducibility and will gain a better understanding of best practises. On the first day, Dr. Celine Carret will draw on her experience as professional editor to illustrate the challenges faced by scientists relating to research integrity and mis-conduct. Specific focus will be given to image manipulation issues and challenges around authorship, plagiarism and conflicts of interest. On the second day, participants will discuss good practices in the collection, analysis and reporting of data to ensure transparency and reproducibility, both in the lab and when sharing results with others in the field. On the third day, Dr. Simon F. Nørrelykke will cover the practical aspects of performing and recording reproducible image and data analysis. This will include hands-on training in creation of figures for publication and documentation of scientific image analysis workflows; demonstrated with the open-source software Fiji. We will also discuss how Deep Learning and other Machine Learning approaches are changing image analysis, in turn making proper documentation more important than ever.
Topics covered will include:
Understand good practices and concepts for experimental planning, data acquisition, storage and sharing
Understand how journals deal with integrity issues and author conflicts
Understand the rights and responsibilities of scientists in the conduct and publication of research
Learn how to handle the practical aspects of reproducible image analysis and figure creation
How to record and share image and data analysis workflows and data, in open-source software
How Deep Learning and other machine learning approaches is changing image analysis and making proper documentation of work-flows even more important
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate during the 3 course days. Moreover, is requires to complete preparatory course work/reading and course exercises (i.e. short presentations, individual assignment) successfully.
1 ECTS (30 learning hours)
Biannually (last: 2019)
Lecturer: Dr. Celine Carret, European Molecular Biology Organization (EMBO), Dr. Simon F. Nørrelykke, Scientific Centre for Optical and Electron Microscopy (ScopeM), ETH Zurich
(2 ECTS) Prof. Nina Buchmann, Dr. Rolf Siegwolf, ETHZ
This course provides an overview about the applicability of stable isotopes (carbon 13C, nitrogen 15N, oxygen 18O and water 2H) to process-oriented ecological research. Topics focus on stable isotopes as indicators for the origin of pools and fluxes, partitioning of composite fluxes as well as to trace and integrate processes. In addition, students carry out a small project during lab sessions. Learning Objective: Students will be familiar with be familiar with basic and advanced applications of stable isotopes in studies on plants, soils, water and trace gases, know the relevant approaches, concepts and recent results in stable isotope ecology, know how to combine classical and modern techniques to solve ecophysiological or ecological problems, learn to design, carry out and interpret a small IsoProject, practice to search and analyze literature as well as to give an oral presentation. Content: The analyses of stable isotopes often provide insights into ecophysiological and ecological processes that otherwise would not be available with classical methods only. Stable isotopes proved useful to determine origin of pools and fluxes in ecosystems, to partition composite fluxes and to integrate processes spatially and temporally.
The participants understand the specific challenges of inter- and transdisciplinary research in general and in the context of sustainable development in particular. They know methods and concepts to address these challenges and apply them to their research projects. The seminar covers the following topics: Theories and concepts of inter- and transdisciplinary research, The specific challenges of inter- and transdisciplinary research, Involving stakeholders, Collaborating disciplines, Exploration of tools and methods, Analysing participants' projects to improve inter- and transdisciplinary elements.
Individual Performance and Assessment: Ungraded semester performance. Active participation during the course days: 24 hours and preparation work for paper presentation in between (36 hours).
2 ECTS (60 learning hours)
Annually (Fall semester)
Lecturer: M. Stauffacher, C. E. Pohl and B. Vienni Baptista, ETH.
for PhD students at ETH: register via MyStudies.
for PhD students at Uni Basel: you have to register as Special student "University of Basel (UBa)" at ETHZ first.
for PhD students at UZH: you have to register as Special student "University of Zurich (UZH)" at ETHZ first.
(1 ECTS), Prof. Enrico Martinoia, University of Zurich
Life exists due to barriers established between the environment and the cell. Biological membranes establish these barriers. The lipid bilayer does not allow hydrophilic molecules such as ions and sugars to cross the membrane. On the other side, proteins embedded in the lipid bilayer are responsible for the selective uptake of constituents into the cell. Within eukaryotic cells compartmentation allows that different processes can occur at the same time in a cell. In this course we will show some techniques, how fluxes between the outside and within the cell can be measured. We will perform classical flux analysis using radiolabelled compounds with yeasts and protoplast and use the patch clamp technique to demonstrate ion currents across the vacuolar membrane.
In this course, we will focus on omics data (mainly genomics and transcriptomics data) and combined data such as GWAS and eQTL. The course is a mixture of theoretical lectures and interactive, practical sessions. The hands-on training will introduce the most commonly applied tools in the field as well as some maybe less commonly but nonetheless very useful ones. Dependent on the participants’ programming abilities we will use GUI-based tools as well as R/Bioconductor and other scripting languages. Learning Outcomes: Understand the process of visual analytics, Know the basics and do’s and don’ts of visualization, Learn how to visualize large-scale genome data, Learn how to visualize transcriptional regulation and abundance, Understand the challenge of GWAS and eQTL data visualization and learn new approaches to address these challenges.
Individual Performance and Assessment: Active participation is expected on all course days (24 hours). Participants will be given practical tasks, their performance will be assessed by their degree of commitment, ability to apply the theoretical concepts to the task in question and creativity. A summary of the completed task and a course diary will have to be handed in after the course (approx. 6 hours effort)
1 ECTS (30 learning hours)
Biannually (last 2019)
Lecturer: PD Dr. Kay Nieselt, Center for Bioinformatics Tübingen, Integrative Transcriptomics, University of Tübingen
(1 ECTS), Christian von Mering, Andreas Wagner, Kentaro Shimizu, UZH
In this course, the theoretical and practical aspects of sequence alignment, phylogeny reconstruction, genome-wide association of phenotypes and genotypes, and more was studies. In doing so, students learned how to generally manipulate data and launch software from the command line, including.
In the field of genomics it is paramount to handle larger amounts of data efficiently, securely, and reproducibly. For this reason, the main objective of this course is to provide students the most basic and most crucial sets of skills to work with genomic datasets. The students will not just learn to manage data and run analysis but also to document their workflow in an easy but reproducible way. The course will also cover different aspects of basic statistical analysis for genomics.
Individual Performance and Assessment: The course will be a mix between lectures and hands-on exercise. Required: attendance, active participation during the lectures and especially the exercises. There is an assignment for each topic that needs to be handed in by the end of the course.
1 ECTS (30 learning hours)
Biannually (last 2019)
Lecturer: Prof. Dr. Anne Roulin (UZH)
This course provides an introduction to statistics ideal for MSc and PhD students in ecology or related fields. Of course, molecular biologists with an interest in statistics are welcome to join as well. Topics treated in this course include: important probability distributions, classical statistical tests (t-test, chi-square-test, U-test), the theory of hypothesis testing (examples: randomisation test and t-test, analysis of variance ANOVA, linear regression (simple and multiple), analysis of covariance ANCOVA, outlook, e.g. GLMs, MEMs. The course will consist of both lectures and computer practicals using the free software package R for statistics and graphics. Participants can bring their own PC or Mac laptops with the latest version of R downloaded from http://stat.ethz.ch/CRAN/ (a small number of computers will be available for those without laptops). The course will be limited to 20 people to allow one-to-one supervision during the computer practical exercises. Prerequisites: Knowledge of the R (or S-Plus) language would be ideal, but is not essential.
Individual Performance and Assessment: Attendance and active participation in the course (16 hours). In order to obtain the credit points, participants are required to hand in an assignment to be carried out at home. The details will be explained during the course. The assignment is due no later than one week after the course has ended. Preparation work for the assignment is 14 hours.
1 ECTS (30 learning hours)
Biannually (last 2018)
Lecturer: Dr. Stefanie von Felten, oikostat GmbH
The aim of the course is to enable participants to design and interpret functional genomics experiments and critically evaluate available technical options. Demonstrations of available technologies at the FGCZ will be included. In the postgenomic era emphasis of research shifts from merely accumulating sequence data towards the identification of functional significance of gene products. The goal of functional genomics is to understand the relationship between genome sequence and phenotype. An important aspect here is the measurement of molecular activities with the high-throughput ‘omics’ technologies transcriptomics, proteomics and metabolomics. The course comprises a theoretical introduction to mass spectrometry, the key technology for protein and metabolite analyses, and to transcriptional profiling. The diverse set of available technologies and most recent developments will be presented, including bioinformatic approaches to analyse data and comprehend large amounts of data.
Individual Performance and Assessment: In order to obtain the credit point, active participation during all three courses days is mandatory.
1 ECTS (30 learning hours)
Every two years (last 2017, next to be announced)
Lecturer: Dr. Bernd Roschitzki, Dr. Endre Laczko, Andrea Patrignani, Dr. Lucy Poveda and Dr. Giancarlo Russo (Functional Genomics Center Zurich)
In collaboration with URPP
This course aims to promote and facilitate the thoughtful and critical use of meta-analysis for research synthesis in ecology by: 1) Explaining the principles and advantages of meta-analysis for research synthesis, 2) Demonstrating the range of applications of meta-analysis in ecology, 3) Promoting understanding of the assumptions and limitations of meta-analysis, 4) Providing first-hand experience in question formulation, data extraction, database design, use of software for meta-analysis and report preparation. The course program includes: Lectures on the history of meta-analysis, types of quantitative research synthesis, conversion of ecological data to effect sizes, and question formulation; combining effect sizes across studies and testing for moderators in meta-analysis (meta-regression), practical on conducting meta-analysis using OpenMEE software; publication bias, dealing with varying research quality and non-independence of observations; format of meta-analysis report, review of case studies of meta-analysis in ecology, and critique of meta-analysis. Practical exercises on data extraction and inclusion criteria and metrics of effect size for their own meta-analysis, testing for moderators; testing for publication bias in own dataset, and considering sources of non-independence.
1 ECTS (30 learning hours)
Biannually (last 2018)
Lecturer: Prof. Dr. Julia Koricheva, UK
(1 ECTS) Prof. Antoine Guisan (U Lausanne), Prof. Niklaus E. Zimmermann (WSL, ETHZ), Prof. Yvonne Willi (U Basel)
The course will be based on a mix of lectures and practicals. The lectures will cover the preparation of data (species data and environmental predictors) for modelling, an introduction to basic and more advanced SDM fitting (e.g. GLM/GAM, CART, and their bagging/boosting versions) and evaluation methods, and how to derive projections to the same or different study areas, or to different time steps, such as future climates. The use of ensemble of models to assess uncertainty will also be covered. Practicals will allow the students to get trained in all these aspects. Due to the limited number of days (2), only an overview of these different aspects will be given and short practicals conducted. Depending on the course progress, there may be scope for individuals to work on their own data sets, so participants are encouraged to prepare their datasets as [species x sites] and [environment x sites] matrices before the course.
The course introduces the study of plant genetic diversity and adaptation using population genomics approaches. Instructor will provide hands-on introduction to data handling, data exploration with summary statistics and data analysis with state-of-the art methods for demographic analysis, population differentiation and selection detection of plant populations. Each topic will be introduced with a conceptual lecture and discussion of recent literature. Students should complete the course with a good understanding of both underlying theory of the most important concepts and practical analysis experience that will enable them to apply these or similar methods to their own research. The data analysis part will use small datasets or the participant’s own data (after consultation with lecturers).
If the corona situation permits, the course will be taught in presence mode or alternatively, as online course.
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate during the 3 course days. Evaluation will be based on a written report that describes the analysis of the given dataset and discusses the result.
1 ECTS (30 learning hours)
Irregular (next 2020)
Lecturer: Prof. Dr. Karl Schmid and Dr. Fabian Freund, University of Hohenheim
This 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. Students 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; and to interpret and evaluate the results in ecological terms. Course Contents will address: - 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); and Randomisation methods.
Individual Performance and Assessment: Graded semester performance.
1 ECTS (30 learning hours)
Annually (Fall Semester)
Lecturer: Dr. Sabine Güsewell
During this capacity building workshop, students will be introduced to the concept of Open Data, Fair Data Principles and Standards, alongside the Open Data Repositories at EU, UZH and ETHZ. Moreover, they will familiarise with a list of key considerations for putting together an Open Data Strategy for their research results. This includes putting together a data management plan, data ecosystem mapping and consultancy for creating data ecosystems for agricultural programmes, building and working with data sharing agreements, data inventories and data trusts. The course includes theoretical input, workshops, consultancy, group and cases study work for data from the following areas: agricultural data, data from breeding research, isotope analysis data.
Individual Performance and Assessment: The following two tutorials should be finished within the course as self-study: The open innovation accelerator (2 hours); the open access author (2 hours). Please register at https://www.fosteropenscience.eu/learning-paths, choose the tutorials and provide the badges that you will get at the end of these tutorials to Romy Kohlmann (romy.kohlmann@usys.ethz.ch).
Additionally, on day 3 of the course there will be a presentation of the group works including the data management plan and the data ecosystem of your own research data.
1 ECTS (30 learning hours)
Last 2020, next to be defined
Lecturer: Violeta Mezeklieva, Data Trainer, Open Data Institute, London UK Stefanie Strebel, Data Services & Open Access, University of Zurich Melanie Paschke, Zurich-Basel Plant Science Center, ETH Zurich
(1 ECTS), Dr. Melanie Paschke, PSC
Online publishing and communicating has become an important channel for scientist to make their research visible, connect with other scientists, and open science to the interested public. Several technologies have popped up in recent years that can support scientists in their publication, communication and self-marketing purposes: open-access journals, research blogs and portfolios, research wikis and professional online networks.
In this two-day workshop, you will learn:
Topics discussed will include:
What is a patent? How is it obtained? What are the implications of Life Science patents for – my career perspectives? – academic research? – society?
1 ECTS (30 learning hours)
Biannually (last 2018)
Lecturer: Prof. H. Müller, University of Basel et al. (organized by Life Science Zurich Graduate School.
NOTE: Please register through Life Science Zurich Graduate School: http://www.lifescience-graduateschool.uzh.ch/en/courses/tsc.html
Tba.
Individual Performance and Assessment: tba.
1 ECTS (30 learning hours)
Annually (NEW: Fall Semester 2022)
Lecturer: Prof Dr. Anne Roulin (UZH)
Next-generation sequencing (NGS) technologies have revolutionized many fields in biology. The Functional Genomics Center Zurich (FGCZ) offers a four-day course with hands-on practicals. The aim is to help scientists interested in NGS technologies, particularly applied to RNA sequencing, to gain a better understanding of the techniques available and their applications. The practical consists of a library preparation starting from polyA enriched RNA, followed by a sequencing run on a bench top sequencer. An introduction to the analyses of the resulting data and some exercises will be offered too. The lectures cover existing and upcoming NGS technologies, their applications and the principles of downstream data analysis. By the end of the course participants should be able to make informed decisions about which technology and workflow to apply to solve specific research questions.
Course Program
Library Prep: PolyA RNA-seq library generation: principles and types
Sequencing: Detailed description of available sequencing technologies platforms, Hands-on laboratory work: preparing and performing sequencing runs
Data analysis: Run QC: Criteria for run performance and quality of data, Preprocessing of the raw data, Mapping the data to a reference, Mapping quality control for RNA-seq data, Transcripts expression quantification and tests for differential expression, Set-based analysis (e.g., pathways, GO-categories) IT and awareness of the data storage and its size
Individual Performance and Assessment: Attendance and active participation during all four days of the course (32 hours) plus completing an individual assignment of around 6 hours.
1 ECTS (38 learning hours)
Biannually (last 2018, next to be announced)
Lecturer: Dr. Lucy Poveda, Dr. Weihong Qi and others, Functional Genomics Center Zurich
The three day interactive workshop is designed to train participants in topics and skills relating to the responsible planning, conduct, analysis and communication of research. During the first two days, participants will explore the principles and challenges of research integrity and reproducibility and will gain a better understanding of best practises. On the first day, Dr. Celine Carret will draw on her experience as professional editor to illustrate the challenges faced by scientists relating to research integrity and mis-conduct. Specific focus will be given to image manipulation issues and challenges around authorship, plagiarism and conflicts of interest. On the second day, participants will discuss good practices in the collection, analysis and reporting of data to ensure transparency and reproducibility, both in the lab and when sharing results with others in the field. On the third day, Dr. Simon F. Nørrelykke will cover the practical aspects of performing and recording reproducible image and data analysis. This will include hands-on training in creation of figures for publication and documentation of scientific image analysis workflows; demonstrated with the open-source software Fiji. We will also discuss how Deep Learning and other Machine Learning approaches are changing image analysis, in turn making proper documentation more important than ever.
Topics covered will include:
Understand good practices and concepts for experimental planning, data acquisition, storage and sharing
Understand how journals deal with integrity issues and author conflicts
Understand the rights and responsibilities of scientists in the conduct and publication of research
Learn how to handle the practical aspects of reproducible image analysis and figure creation
How to record and share image and data analysis workflows and data, in open-source software
How Deep Learning and other machine learning approaches is changing image analysis and making proper documentation of work-flows even more important
Individual Performance and Assessment: In order to obtain the ECTS points, participants are required to actively participate during the 3 course days. Moreover, is requires to complete preparatory course work/reading and course exercises (i.e. short presentations, individual assignment) successfully.
1 ECTS (30 learning hours)
Biannually (last: 2019)
Lecturer: Dr. Celine Carret, European Molecular Biology Organization (EMBO), Dr. Simon F. Nørrelykke, Scientific Centre for Optical and Electron Microscopy (ScopeM), ETH Zurich
Phylogenetics and phylodynamics are central topics in modern biology. Phylogenetic inferences reconstruct the evolutionary relationships between organisms, whereas phylodynamic inferences reveal the dynamics that lead to the observed relationships. These two fields have many practical applications in disciplines such as epidemiology, developmental biology, paleontology, ecology and even linguistics. However, phylogenetics and phylodynamics are complex and fast-evolving fields. As such, inference tools are not easily accessible to researchers who are not from a computational background. Taming the BEAST is a summer school focusing on the BEAST 2 software and consisting of a mix of invited talks, lectures and hands-on tutorials by leading and renowned experts in the field (including several of the core developers of BEAST 2). The aim of this summer school is to equip participants with the skills necessary to confidently perform their own phylogenetic and phylodynamic inferences in Bayesian settings, while providing them with a firm grasp of the theory behind those inferences. Participants are also highly encouraged to bring their own datasets along and to engage with the organizers and speakers to address any problems specific to their own datasets/analyses.
Individual Performance and Assessment: Students are required to complete all tutorials assigned during the workshop in order to receive course credit.
2 ECTS (60 learning hours)
last 2021, next to be announced
Lecturer: Dr. G. Singh Bhullar, FIBL; Dr. Franz Bender, Agroscope; Dr. Frank Liebisch and Dr. Melanie Paschke, ETH Zurich