Programme-related courses

To obtain a broad overview and understanding of “the green sector” in the Netherlands and abroad, with the focus on the plant breeding industry and biotechnology, the role of fundamental research therein, and job opportunities for young MSc’s with a plant molecular biology/biotechnology background.

This course will teach you to design using the biomimicry design method. The course will have both individual and group work. The course will start with a series of workshops that will get you going in the design process. Gradually during the design process, you will learn to make choices independently as a group based on the progress you make with the design. At the end of the course, groups deliver a conceptual design embedded in a report, supported by a video pitch and poster presentation. You learn how to produce a report that informs designers and engineers on how to materialize the biology embedded in the design. 

* Every Tuesday and Thursday afternoon in period 1. 

The aim of the course is to introduce you to bio inspired approaches and the philosophy behind it. In addition, you will learn and apply a Life Cycle Analysis (LCA), construct a Business Model Canvas (BMC) and perform an Ecological Quick Scan. This will help you to function in a multidisciplinary team as a biologist at a design and innovation table. 

In this course, you will learn how to design (parts of) a system using bio-inspired design methods & techniques.
 
You will receive workshops to practice the use of bio-inspired techniques and apply these to a specific design case.
 
You will work together in groups of about 4 people with different educational backgrounds.

Over the course we will pay attention to nature-inspired techniques for design and evaluation of design, including design principles, roadmapping, circular BMC and surrounding scans.
 

Plant-microbe interactions will be introduced in a general lecture, highlighting recent developments and the importance of the reviewing process. For a set of recent manuscripts the students will act as reviewers and editors following the format provided by high standard international journals. Editor decisions will be presented and discussed. 

In this obligatory course you will be introduced to all topics within biofabrication and regenerative medicine to provide you with a broad basic knowledge on the theoretical background, current status and future perspectives of the field. Besides the theoretical parts, you will work in teams on literature presentations and on creating your own research proposal.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Tissue engineering (TE) is an ever-growing multidisciplinary scientific field aiming at replacing injured, missing or damaged tissue. This course teaches Master students’ in-depth and hands-on knowledge on developmental and adult blood vessel formation in health and disease and the current clinical treatments for which vascular(ized) TE is thought to be eligible. Moreover, we will address state of the art techniques of vascular(ized) TE, including the use of biomaterials and cell sources for bioreactor-cultured and in situ applications.

Please note:

This is an online course stretching over 7 weeks with a study load of approximately 9-10 hours per week. Please take into account that the studyload is divided over the week so you will need to be able to login on various moments (taking into account vacation days).

Registration:

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Maximum number of participants is 32 students.

Students from outside Utrecht University can register for this course by sending an email to m.m.krebber-2@umcutrecht.nl. Please include your name, student number, Master’s programme and the course code.

Effective mining and integration of data is one of the major challenges in biomedical research. Decades of research led to numerous databases, including important resources such as NCBI, SWISS-PROT and ENCODE. Here we outline current data integration challenges in biology and biomedical research and discuss state-of-the-art approaches for tackling these challenges.

Due to limited capacity, Master students with the Bioinformatics Profile will receive preferred placement in this course.

Course moved to Period 3.

Effective mining and integration of omics data is an important part of biomedical research. Decennia of research led to numerous tools and databases, including prominent resources such as the HumanProteinAtlas and ENCODE. Here we outline current data processing and integration methods within omics research and discuss state-of-the-art data analysis.

Many researchers will need to apply statistical analysis in their work. Often, the R statistical language is chosen, since it is well established, free, and has many packages available for different tasks. If you want to be able to use the more powerful features of R, create visually attractive figures with ggplot, write concise and organized code that you can share with others, create automatically generated reports. This course gives you the knowledge to follow one of the subsequent courses of statistical analysis for omics technologies, and linear models with R.

This course is aimed at master and PhD students who want to understand and design data analytic methods for interpretation of genome-wide biological data (i.e. Omics data). (This course can also be followed as part of the UBC/GSLS Bioinformatics Profile). 

Registration:

Bioinformatics Profile students will have priority when this course is followed as a part of their profile. Thereafter, registration is on 'first-come-first-serve' basis until the maximum number of 20 participants is reached.

Modern biology is largely a data-driven enterprise. We collect genomic information on thousands of patients and matched controls to find genomic causes for illness using GWAS, easily collect expression of (tens of) thousands of genes at different time points and under different experimental conditions to understand what makes a system tick, and with the rise of single-cell omics the datasets are larger and more specific than ever before. Our minds are formidable pattern recognition devices, but they are biased in various ways and not equipped for these huge datasets. How can we use all this data to build good predictive models, or automatically order data so that we can gain new insights?

Enter Machine Learning. In this course, we start with the basics: what is the difference between supervised and unsupervised learning, how do we formulate something that the computer can optimise on its own given training data, and how do we then iteratively optimise this? With these basics of cost functions and gradient descent under our belt, we then look at several well-known algorithms and implement them ourselves using only Python, numpy and pandas to gain in-depth understanding in the first week, before moving on to the modern scikit-learn library which does all the heavy lifting for you in the second week. We top it off with a group project on a biological dataset where your team tries to build the best classifier for that dataset. Along the way we look at clustering and dimensionality reduction, and gain cursory knowledge of linear algebra, which is the language that machine learning algorithms are formulated in and which you will use to do so as well.

When you are done with this course, you should be well-equipped to independently learn about more complex classifiers (Random Forests, convolutional neural networks, etc.) or unsupervised methods, and to apply ML to real-world biological problems. This course also lays the foundations for the more theoretical and higher-level understanding you’ll gain in Analytics and Algorithms for Omics Data (BMB508219). 

During this course, the emphasis will be on the essential abilities and knowledge that is required to be able to become a skilful bioinformatics researcher. A broad range of topics, varying from computer skills and programming, data analysis and visualisation to computational algorithms, will be addressed and put into perspective using real-world biological research questions and problems.

Construct, root and interpret phylogenetic trees; for a given protein, find its homologs, annotate its protein domains, time its duplications, define its orthologs, pinpoint its origin.

In this course, attention is paid to understanding and working with large amounts of data as has been obtained in recent years in many genetic and molecular research. These technological developments require new skills and concepts to be able to understand and conduct life science research. In two parts, we work successively with mutations and sequencing data, the regulation network is studied and how the consequence of mutations in proteins can be better explained through evolution.

The course covers a large number of mathematical models to show how one can describe and understand the dynamics of biological populations. Examples of this population dynamics are: ecological food chains, epidemiological models, bacteria infected by phages and populations of cells. Students are made familiar with the preparation and analysis of mathematical models. 

In this course the students will get familiar with current bioinformatics tools to detect, visualize and interpret genomic alterations in tumors. Current advances in cancer genomics research will be presented in guest lectures and paper discussions.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 30.

The modeling of real biological systems can aid greatly in the understanding of the behavior of such systems, and in predicting how they will behave under all kinds of circumstances. In this course, we will study how to build models using differential equations, and how to analyze their behavior.

We will use a context of diverse examples from biology, including ecological growth, predator-prey systems, enzyme reactions, genetic regulation, animal coat patterns, and firing neurons. 

Models are built from the ground up, using biological knowledge and mathematical tools, enabling the students to gain the experience necessary to build their own models, analyze them, and valuate their worth. 

*This is an e-learning course, which can be followed any moment through the year.*

The course Introduction to Research Data Management gives practical insights on Data Management for scientists. Basic knowledge of relational databases, entity-relationships models, relational models and SQL with MySQL is provided during the course. The programming language used to process data from and to the database is Python.

During the course, the emphasis will be on composing and analysing exact models based on specific hypotheses. The results of the analyses offer an understanding of the original biological system. The models studied address fundamental questions from a variety of biological fields.

In this course you will learn how to analyse genome data of individual microbes, but also of microbial communities (metagenomics).

Computational structural biology is a mature field of research whose contribution to life sciences is becoming increasingly more appreciated. The aim of this course is to provide a solid basis of computational structural biology methods, with an emphasis on practical protein modelling and simulation, to interested MSc and PhD students in the life sciences. Further, given the lack of emphasis on practical computational research in MSc and PhD courses, this course is designed to have a smooth learning curve regarding the GNU/Linux environment and its command-line interface. By the end of the course, the students are expected to master the three major computational structural biology methods – homology modelling, molecular dynamics, and protein docking – not only from a user perspective but also from a theoretical standpoint.

Starting with clinical cases, the pathophysiology of infectious and immune diseases will be presented. New concepts and therapies will be discussed.

Registration
Please send an overview of your previous knowledge in I&I to secretary.iimaster@umcutrecht.nl and register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 45.

This course covers different molecular and cellular approaches applied in the study of the healthy and diseased heart. With respect to cardiac disease, topics that will be discussed include sex differences, microRNA expression, adrenergic signalling, and calcium regulation. Moreover, the molecular basis of arrhythmias (either inherited or acquired) will be featured from different view points as well.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide. The maximum number of participants is 50.

Students are familiarised with regenerative medicine in cardiac diseases. Topics include cardiac development, reprogramming, and RM treatment options. In addition, students are introduced in the interpretation and processing of study data, and get acquainted with the impact of research on society, in particular on patients.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

In this course, we focus on the role of the immune system in atherosclerotic disease and manifestations of this disease like myocardial infraction. Special attention will be given to the different types of immune cells and their role in atherosclerosis, plaque rupture and acute coronary syndrome.

Registration:

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide. The maximum of participants is 40. Prioritisation of acceptance is based on:

1. Students from abroad
2. BoD students that follow the cardiovascular track
3. Other BoD students
4. GSLS students
5. Students from other Dutch universities

This course is intended for non-neuroscience master students who would like to get more background in neuroscience. The lectures during the course cover a broad range of neuroscience topics from gene to neurological disease.

Registration
Please be aware this course code is offered online as well. For this Face-2-Face version be sure to select the correct Block: BMS_P1_A.

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

This course gives you a unique opportunity to study the state of the art insights in Neurosciences, discover the research strengths of UMC Utrecht and experience our educational philosophy.

Registration:
Please be aware this course code is offered face-2-face as well. For this Online version be sure to select the correct Block: BMS_P2_A.

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Students from outside the Graduate School of Life Sciences can register for this course by sending an email to L.vanOudenaarden@umcutrecht.nl. Please include your name, student number, Master’s programme and the course code.

You are in your first weeks of Biology of Disease, the starting point of your science-related career. How will you prepare for this career? What do you need to know, develop, and learn to become successful in this science-related world? Together with your fellow BioD-ers you will think about these questions.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

In this course physiology and pathophsyiology of organs (heart, vasculature and kidney) are taught including their relations and interactions.

This course is a self-regulated learning course. Meaning that students need to acquire knowledge that is provided in online lectures and in the study book. Students apply this knowledge to written assignments that are available on blackboard.

The exam is scheduled in November 2022. The exact date and type of assessment will be announced on Blackboard.

This course focuses on endocrine and metabolic processes, and in particular their dysregulation in cancer and type 2 diabetes mellitus. Lectures and tutorials in the first week discuss the molecular mechanisms in the liver, pancreas, brain and fat tissue that are involved in regulating glucose and fat homeostasis.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

CS&D students (max. 20) and Biology of Disease students (max. 20) and other GSLS students.

This course will offer a mix of General Pathology and Specific (organ-related) Pathology. The four major subjects are Cell pathology, Inflammation, Tumors, and Cardiovascular pathology.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The course will elaborate on the mechanisms that prevent bleeding after injury (haemostasis) and the role of these mechanisms in the etiology of arterial and venous thrombosis. The biology of coagulation and the interaction between the vascular wall and circulating blood (cells) will be explained.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Tissue engineering (TE) is an ever-growing multidisciplinary scientific field aiming at replacing injured, missing or damaged tissue. This course teaches Master students’ in-depth and hands-on knowledge on developmental and adult blood vessel formation in health and disease and the current clinical treatments for which vascular(ized) TE is thought to be eligible. Moreover, we will address state of the art techniques of vascular(ized) TE, including the use of biomaterials and cell sources for bioreactor-cultured and in situ applications.

Please note:

This is an online course stretching over 7 weeks with a study load of approximately 9-10 hours per week. Please take into account that the studyload is divided over the week so you will need to be able to login on various moments (taking into account vacation days).

Registration:

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Maximum number of participants is 32 students.

Students from outside Utrecht University can register for this course by sending an email to m.m.krebber-2@umcutrecht.nl. Please include your name, student number, Master’s programme and the course code.

Effective mining and integration of data is one of the major challenges in biomedical research. Decades of research led to numerous databases, including important resources such as NCBI, SWISS-PROT and ENCODE. Here we outline current data integration challenges in biology and biomedical research and discuss state-of-the-art approaches for tackling these challenges.

Due to limited capacity, Master students with the Bioinformatics Profile will receive preferred placement in this course.

Course moved to Period 3.

Effective mining and integration of omics data is an important part of biomedical research. Decennia of research led to numerous tools and databases, including prominent resources such as the HumanProteinAtlas and ENCODE. Here we outline current data processing and integration methods within omics research and discuss state-of-the-art data analysis.

Many researchers will need to apply statistical analysis in their work. Often, the R statistical language is chosen, since it is well established, free, and has many packages available for different tasks. If you want to be able to use the more powerful features of R, create visually attractive figures with ggplot, write concise and organized code that you can share with others, create automatically generated reports. This course gives you the knowledge to follow one of the subsequent courses of statistical analysis for omics technologies, and linear models with R.

This course is aimed at master and PhD students who want to understand and design data analytic methods for interpretation of genome-wide biological data (i.e. Omics data). (This course can also be followed as part of the UBC/GSLS Bioinformatics Profile). 

Registration:

Bioinformatics Profile students will have priority when this course is followed as a part of their profile. Thereafter, registration is on 'first-come-first-serve' basis until the maximum number of 20 participants is reached.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

In this course the students will get familiar with current bioinformatics tools to detect, visualize and interpret genomic alterations in tumors. Current advances in cancer genomics research will be presented in guest lectures and paper discussions.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 30.

This course allows students to acquire basic and advanced knowledge on membrane traffic and its relationship to disease and development, and ask the students to focus on the membrane traffic defect(s) in a given disease.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

This course will address the molecular basis for correct chromosome segregation during cell division. Defects in this process give rise to aneuploidy and many contribute to carcinogenesis.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Maximum number of participants is 30.

This (combined AIO - Master students) course features a number of seminars by renowned scientists in the field of Signal Tranduction in Cancer Biology

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The course aims to provide an understanding of concepts of developmental biology and genetic analysis. In addition, the course teaches a variety of skills, including critical reading and group discussions.  Having completed a Bachelor’s level genetics course is required. This course is an advanced genetics course.

Registration
Arrangements have been made to accomodate that this course can be attended if you also attend the course Introduction to Bioinformatics for Life Sciences.

In this course we will focus on what you can do and what you shouldn’t do to get the best representation of your digital image without altering the actual data. The course will be given in an interactive way, with time for practice.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Maximum number of participants is 25.

This course will teach the crucial concepts of regulation of gene expression, with a focus on the process of transcription at the molecular level, but also including concepts derived from cellular, developmental and disease states.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 40.

This course provides the students with a broad overview and background in all research topics, techniques and model systems that represent the research school “Cancer, Stem Cells & Developmental Biology”.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

This course can be considered a general introduction to bioinformatics and provides an overview of the importance of bioinformatics in various biological disciplines, with a focus on the research that is performed at Utrecht University. The theory and tools for bioinformatics provided are very useful for any life science researcher. 

This one-week course aims to give an overview of techniques used in proteomics, particularly mass spectrometry, along with examples of their application to biological research.

This course is aimed at Master and PhD students who want to explore computer-assisted methods for interpretation of biological data and develop their programming skills.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

CS&D and MCLS students have priority to this course. Thereafter, registration is on 'first-come-first-serve' basis until the maximum number of 45 participants is reached.

The aim of this course is to give a basic training in R for Life Sciences students. R is a programme for statistical analysis.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 45 students per course.

*This is an e-learning course, which can be followed any moment through the year.*

The course Introduction to Research Data Management gives practical insights on Data Management for scientists. Basic knowledge of relational databases, entity-relationships models, relational models and SQL with MySQL is provided during the course. The programming language used to process data from and to the database is Python.

This course will address both fundamental mechanisms regulating stem cell function as well as considerations concerning the use of stem cell therapies in the clinic.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Maximum number of participants is 60 students.

This course focuses on endocrine and metabolic processes, and in particular their dysregulation in cancer and type 2 diabetes mellitus. Lectures and tutorials in the first week discuss the molecular mechanisms in the liver, pancreas, brain and fat tissue that are involved in regulating glucose and fat homeostasis.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

CS&D students (max. 20) and Biology of Disease students (max. 20) and other GSLS students.

Not taught in 2022/2023

Genetic analysis in model organisms is a powerful approach to gain detailed insight into biological processes. In this course, we will highlight five different model organisms that cover different aspects of biomedical research and provide a basic understanding of genetic analysis in these model systems.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

Maximum participants is 25 students

Please Note: Zebrafish in Development, Organogenesis and Disease is given once every 2 years. Not taught in 2022/2023

This course will focus on five specific areas of current zebrafish research, angiogenesis and bone development, signal transduction pathways in body formation, the role of microRNAs in embryogenesis, heart development, and use of the zebrafish as a cancer model.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The aim of this course is to provide students with state-of-the-art knowledge of interest for the construction of complex organic molecules and architectures. Examples of systems of relevance for advances catalysis, the material sciences and the life sciences will be discussed and studied in detail. Intimately related to these objectives is the introduction of the students to advanced models required for the planning of complex multi-step syntheses (strategies), the interpretation of experimental data, the elucidation of underlying reaction mechanisms, stereochemical consequences, etc.

The field of chemical biology lies at the interface of chemistry and biology. It uses chemistry, chemical principles, and notably molecules to study and solve important issues in biology. The course will focus on chemical and biological syntheses and behaviours of relevant molecules for chemical biology, primarily carbohydrates, peptides and nucleic acids, as well as their uses in addressing biological questions. Bio-orthogonal reactions and the use of the compounds derivatized as chemical probes will also be discussed. This course will also have an emphasis on critical reading of recent literature and presentation on this to the group.

Are we in danger of falling back to the pre-antibiotic era? Can we deal with epidemics/pandemics of Ebola, Zika, Corona and Influenza virus? When will parasitic diseases like Malaria and Schistosomiasis be eliminated? What can you do yourself? These questions will be addressed in this course. A challenging assignment, to design a drug candidate against a disease of choice, forms the core of this course. The course is given entirely online, and at your own pace, so you can do it during your minor or major traineeship, even from abroad.

Subjects of the course are:parts of virology/bacteriology/parasitology/immunology, organic chemistry, biochemistry, pharmacology, pharmacokinetics, structural biology, and especially computational medicinal chemistry.
 
In this course, we challenge the student to think of a medical need, to find a target, to come up with a lead and to optimise this lead towards a drug candidate by means of molecular docking. You present the medical need and target in a prerecorded presentation and write a final report on your own drug candidate..

In this course you will study the process of drug development and drug regulation, both processes that are an essential part of the drug pipeline. There will be an emphasis on new innovative drugs and therapies like novel vaccins, miRNA, antibodies, and gene- and stem cell therapy. 

The consecutive steps of the current paradigm are discussed following the course book of H.P.Rang. We begin with the history of Drug Discovery. Then we discuss choosing the project; choosing the target, finding a lead, and optimising the lead. Supporting workshops will deal with bioinformatics, computer-assisted drug discovery, and quantitative pharmacology. You will spend almost half of your time in a team in order to present an innovative research proposal. 

This course provides you with insights in the immunological processes of chronic inflammatory diseases, such as asthma, COPD, IBD, allergies, and autoimmune diseases. 

This one-week course aims to give an overview of techniques used in proteomics, particularly mass spectrometry, along with examples of their application to biological research.

Characteristics of nanoparticles such as size, surface area and internal composition make them attractive candidates for use in therapeutic and diagnostic applications. The aim of this course is to provide an overview of the nanomedicine field. Every week a theme will be discussed in which nanomedicine is involved: therapeutics (both synthetic and bio-inspired) and diagnostics. We will focus on the applications of nanomedicine in cardiovascular disease and cancer. 

Medicine are amongst the most regulated products in society. From the earliest pre-clinical stages onward, policy makers want to foster the development of safe, effective and affordable medicines for patients in need of pharmacotherapy. When a drug reaches the market, it is the beginning of a process of complex interactions between patients, prescribers, insures, pharmaceutical companies and governments. Pharmaceutical policy analysis may provide the much needed evidence to inform policy and decision makers involved in ensuring access to medicines from bench to bedside. 

In this course, you will gain insight in the framework(s) defining access to medicines and all stakeholders involved. The course will specifically focus on Regulation, Pricing & reimbursement and Responsible use. Furthermore, you will develop a better understanding of analytical approaches in pharmaceutical policy analysis using these three themes as learning devices.

The course is centered around the project of independently conducting a pharmacoeconomic analysis in a group of 3-4 students. At the same time, the block provides a broader picture of the place of such pharmacoeconomic analyses within the broader health policy field. 

During this course you will work in a small group (2-3) to perform a complete cycle of pharmacoepidemiological research. A protocol has to be written, data has to be prepared, statistical analysis has to be performed, a scientific publication has to  be written and finally the research has to be orally presented. Each group will be supervised by a researcher of the division of Pharmacoepidemiology & Clinical Pharmacology.

During this course we will try to achieve the starting level for the Drug Innovation Master’s programme. We will offer workshops on the topic of "Understanding Drugs", encompassing the fields of bioorganic chemistry, pharmacokinetics, pharmacodynamics, pharmaceutics, anatomy and physiology, biochemistry, analytical chemistry, and pharmacotherapy.

To obtain a broad overview and understanding of “the green sector” in the Netherlands and abroad, with the focus on the plant breeding industry and biotechnology, the role of fundamental research therein, and job opportunities for young MSc’s with a plant molecular biology/biotechnology background.

Please note: Basic of Biostatistics is an online course (~16 hours per week). The course offers a variety of learning activities such as web lectures, discussions and (group)assignments. A maximum of 60 students can be enrolled in the course (divided into groups of max 15 students in order to remain small-scale learning).

The course provides an introduction to statistical methodology and supplies a number of statistical techniques important for practical data analysis. Examples from the medical and biological fields will be used in exercises.

NOTE: It is expected that students have some basic knowledge on descriptive statistics and mathematics.

Course schedule
The statistical theory will be introduced and discussed in the first 6 weeks (week 46 till 51). After the Christmas holiday (week 52 till 1) the remaining parts of the course are scheduled: case study (week 2) and exam (week 3). The re-exam is scheduled in week 6. You will find the more detailed schedule in the Osiris course catalogue.

Registration
You can apply for this course via Osiris Student. You will be able to register for this course in Osiris Student during a fixed time frame. See the information on the Study Guide. Registration for the course will open in the second half of September.

This course is an introduction in Biotechnology. It will give an overview of different fields in biotechnology (molecular techniques, bacterial biotechnology, fungal biotechnology, plant biotechnology, industrial biotechnology, medical biotechnology, animal biotechnology) with special emphasis on new developments. In addition, other aspects related to biotechnology, such as intellectual property rights, ethical concerns and the marketability of a product are discussed.

*9 weeks of 20 hours per week

The aim of this course is to strengthen your expertise in plant-, microbial and landscape ecology and to show how this expertise is of vital importance to natural resource management. 
 

The course focuses at behavioural and welfare problems in animals. It addresses the (neuro)ethological basis, the implications for science and society, and clinical aspects.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 26.

To register the applicants are asked to send a short (max. 250 words) motivation letter to the course coordinator Vivian Goerlich-Jansson (v.c.goerlich-jansson@uu.nl). In the letter please explain why you want to take part in this course and why it is relevant for your further studies/career. A selection will be made based on the timing of registration (first come, first serve) and the motivation letter.

In this course all aspects of sexual behaviour will be presented on the basis of the book "The Red Queen, Sex &The Evolution of Human Nature" of Matt Ridley, 1993, key papers and recent articles. Although the title of the book suggests differently, the major part of the book deals with animal behaviour. Human behaviour is also treated from a biological point of view.

Being involved in research, MSc students should be aware of the potential role their results could play to build a sustainable future. Moreover, students should be able to constructively discuss and connect with other students of the master's program. As such, this inter-track course will encourage the participants to determine and discuss how their research topic may contribute to solving questions related to sustainability. In particular, participants will put their research in relation with one or more of the 17 Sustainable Development Goals set by the United Nations (https://sustainabledevelopment.un.org/?menu=1300). Groups of students belonging to different tracks will be composed. Based on the project proposal that the students wrote at the start of their major internship, participants will write a short report containing a clear description of their potential contribution. Each participant will read the reports of a few fellow peers and give peer review. Based on group meetings and discussion of the reviews, each group will choose one report which will be presented in plenary in no more than two slides at the end of the course.

The aim of this course is to discuss and understand principles of the ecology, physiology, molecular biology, developmental biology of fungi and biotechnology with fungi. To this end, students will make assignments, discuss articles, have lectures, participate in the annual meeting of the section Mycology of the Royal Netherlands Society for Microbiology, make summaries of scientific presentations, and interview an expert in the field of fungal biology.
 

This course can be considered a general introduction to bioinformatics and provides an overview of the importance of bioinformatics in various biological disciplines, with a focus on the research that is performed at Utrecht University. The theory and tools for bioinformatics provided are very useful for any life science researcher. 

The aim of this course is to give a basic training in R for Life Sciences students. R is a programme for statistical analysis.

Registration

You can register for this course via Osiris Student. More information about the registration procedure can be found here on the Studyguide.

The maximum number of participants is 45 students per course.

*10 weeks of 20 hours per week

The course is a reflection on and exercise in natural resources management in its societal context. The emphasis is on the application of what you already know, what you are able to do in the field of natural resources management and on learning by doing. The main activity of the course consists of working on two major assignments.

The purpose of this course is to acquire working knowledge of the methods for measuring and analysing animal behaviour. The course is based on the book "Measuring Behaviour. An introductory guide".

Registration:
The maximum number of students is 25. Applications are on "first come first serve" basis.

In this course you will learn how to analyse genome data of individual microbes, but also of microbial communities (metagenomics).

Plant-microbe interactions will be introduced in a general lecture, highlighting recent developments and the importance of the reviewing process. For a set of recent manuscripts the students will act as reviewers and editors following the format provided by high standard international journals. Editor decisions will be presented and discussed. 

A general lecture on plant-environment interactions will set the stage for an advanced-level course on how plants adjust to their most important environmental factor: light. Although plants rely fully on light as their energy source, they often struggle with temporal and spatial variations in the abundance of this resource. Both excess and shortage of light can be very harmful to plants. Students will study the latest developments in plant plasticity towards variations into light quality and quantity. 

The master classes consist of three lectures with subsequent discussion, each with their own topic: 1. Morality, 2. Empathy, and 3. Culture in nonhuman primates. Students will read primary literature to prepare each class and its discussion. The classes will be examined with a multiple choice exam.

Send an e-mail to the course coordinator masterclass.bio@uu.nl for enrollment.

The aim of this course is to discuss and understand principles of the ecology, physiology, molecular biology, developmental biology of fungi and biotechnology with fungi. To this end, students will discuss articles, have lectures, participate in the annual meeting of the section Mycology of the Royal Netherlands Society for Microbiology, and make summaries of scientific presentations.

This course approaches this broad field of research from a zoo perspective, and will mainly focus on areas of interest that are related to small population management in captive settings and in field conservation programs.

Registration:
2^nd year BE students have priority, followed by 1^st year BE students. Other GSLS students have to apply with a motivation letter. The maximum number of participants is 20.

Register here.

Diagnostic research in the past focused particularly on estimating the sensitivity and specificity of individual diagnostic tests. This course will demonstrate that this so called 'test research'  is not necessarily the same as diagnostic research. Furthermore, we will widen the horizon by proposing modern methods of diagnostic research and data analysis in which a patient's test result can and should be considered in the context of other patient characteristics or test results. These methods enable 1. direct estimation of individual probabilities of disease presence based on all diagnostic information and 2. evaluation of the extent to which a particular diagnostic test has true added value in the clinical context. Also, conventional and advanced methods for systematic reiews of diagnostic tests will be presented.

Max. 60 participants. 

Register here.

This course will address two important topics in causal epidemiologic research, namely confounding and effect modification. These topics will be discussed in the context of both etiologic research and observational intervention research. Effect modification and confounding are difficult concepts to understand and often mixed up. In this course the theory as well as the practical side of these issues will be discussed.

Max. 60 participants. 

Register here.

Max. 20 participants. 

Summer School. Register here(link is external).

Max. 50 participants. 

Register here(link is external).

The objective of the course is to provide the participant with insight in the principles and important issues of cardiovascular disease epidemiology. Topics that will be covered are:

• Atherosclerosis, the underlying pathology for the most common cardiovascular diseases;
• Risk factors for cardiovascular disease;
• Worldwide trends in cardiovascular disease morbidity and mortality;

In addition, there will be several key lectures given by invited speakers from both inside and outside the UMC Utrecht. During these lectures the latest developments in CVD epidemiology will be presented. Topics in key lectures may include sex differences in CVD, the importance of genes and environmental factors in CVD.
Interactive teaching is key in this course. Apart from active participation during the lectures, the participant will be assigned to tasks: First, an individual assignment about cvd research in 2030 has to be made and second particpants have to defend a proposition in a debate. This will be a group assignment.

Register here(link is external).

This course covers the basic applications of biostatistics in the analysis of medical research data.

Register here(link is external).

In clinical epidemiology, research is focused on questions of diagnosis, prognosis, treatment and etiology. To address these questions, several research options are available, including intervention trials and case-control studies using data obtained in a clinical setting.
In the course, the principles and practice of clinical epidemiology will be considered and examples from the literature will be worked out and discussed. The aim is to provide the participants with the knowledge to evaluate and judge applied clinical research and data analysis and give a sufficient scientific and methodological background to actively participate in clinical studies.

Topics are: principles of applied clinical research, study design and analysis of diagnostic and prognostic research, study design and analysis of comparative (clinical) experimental and non experimental studies.

Register here(link is external).

A clinical trial is an exceedingly important instrument in the assessment of treatment efficacy. With regard to clinical trials, the emphasis will be on methodological principles and on the clinical practice of therapeutic experiments. Furthermore, this course addresses the principles of studying the effects of drug treatments on the risks of unintended effects. The accent is on proper formulation of the research problem with a view to clinical and regulatory relevance of the study results, and on requirements for validity in non-experimental research.

The course program covers the principles of therapeutic research design, including design of study, design of data collection, design of data analysis, including some modelling techniques in the analysis to clinical trials, and the interpretation of its results. Finally the program covers the principles of drug risk assessment in the context of therapeutic research. Seminal lectures on trials and practical exercises are included in the program.

Register here(link is external).

Computational statistics concerns the development, implementation and study of computationally intensive statistical methods. Such methods are often used e.g. in the fields of data visualization, the analysis of large datasets, Monte Carlo simulation, resampling methods such as the bootstrap, permutational methods, Markov Chain Monte Carlo methods and various numerical methods of equation solving such as the EM algorithm and Newton-Raphson iteration. A very powerful tool to implement such methods is the R statistical programming language.

This course will present essential methods in computational statistics in a practical manner, using real-world datasets and statistical problems. Examples will include e.g. 1) evaluating and comparing the performance of different statistical techniques in a specific setting using simulation, 2) implementing complex methods such as an EM algorithm to fit a joint model, 3) implementing the bootstrap to obtain a standard error estimate which is not available in closed-form. We will also develop advanced R programming skills.

Register here(link is external).

Max. 20 participants. 

Register here(link is external).

Infectious diseases are an important cause of disease burden in animals, as well as humans. Infectious animal disease epidemiology is important in both a veterinary.

You will learn techniques and theory of veterinary epidemiology of animal infectious diseases, including mathematical modelling, design and analysis of infectious disease animal transmission experiments, infectious disease risk mapping, risk assessment and disease surveilllance.

Register here(link is external).

Infectious disease epidemiology is targeted towards understanding the routes and risks of transmission of pathogens between humans, and from the envrionment to humans, and using this knowledge to design and evaluate the effectiveness of interventions. This is a dynamic interplay between pathogens and humans, which clearly distinguishes infectious disease epidemiology from the epidemiology of non-communicable diseases, such as cardiovascular and oncology. We will introduce epidemiological methods and techniques that are specific for infectious diseases, such as outbreak investigations and (sero)surveillance. Specific (classes of) infectious diseases and their epidemiology will be covered. Other topics of the course include interventions such as vaccination, and antimicrobial resistance.

Summer School. Register here

Register here(link is external).

The generalized linear model (GLM) is a flexible generalization of ordinary least squares regression. The GLM allows the linear model to be related to the response variable via a link function together with an error function. Starting with the familiar linear regression and ANOVA, the course will expand the linear model to include link functions such as the logit with binomial and the log with Poisson error distributions, thereby enabling students to model outcome variables that are not continuous. Attention will be paid to likelihood estimation methods and the checking of model assumptions.

Register here(link is external).

In modern health research genetic association studies play a large role. Genome-wide association studies are being performed to discover genetic variations associated with both continuous traits and diseases. Results from these studies are subsequently being used to better understand the mechanisms that lead to diseases, and to understand whether associations found in observational studies between risk factors and diseases are indeed causal.

This 5-day course covers a short introduction to population genetics. During the course we will discuss genome-wide association studies (GWAS), genetic imputation. Also we will show how to follow-up the hits identified in GWAS studies. Then we will discuss Mendelian randomization studies and some miscellaneous topics. Some basic knowledge on epidemiology and population genetics is preferable. We end the course with an exam.

Register here(link is external).

This course offers you the opportunity to practice and improve your skills in analyzing (animal) health data from structured populations. You will perform statistical analyses on a dataset provided by the teachers or on your own data. You will go through the process of formulating a hypothesis, analyzing data, interpretation of the results, and reporting.

During the course you will be guided while working on this project by epidemiologists and statisticians. The week ends with presenting the results of your work both written and orally.

Register here(link is external).

Statistical inference is intended to aid in answering scientific questions about a population, based on a sample from this population, i.e. on data that are subject to variability. The data generating mechanism is described as a probability model that is completely specified except for a limited number of unknown parameters. The questions that can be answered are a) are the data consistent with the model? and b) assuming that a) is fulfilled, what can be concluded about values of the unknown parameters? In this course, the basic principles of statistical inference are presented, with an emphasis on likelihood methods. Methods are illustrated by the classical linear model.

Register here(link is external).

This course provides insight in the basic terminology and principles used in epidemiology. The course starts with the history and design of epidemiological research, and the different measures of frequency and association. Also, the principles of bias and confounding are addressed. In the second part of the course, epidemiological fields of research as covered at UMC Utrecht and Utrecht University are presented.

Register here(link is external).

This course provides basic knowledge of statistics. The course is aiming to level differences in prior knowledge among students and provide the necessary base for the next two statistical courses in the MSc Epidemiology programme.

Register here.

Learn the basics of machine learning, with a special focus on sparse data as they occur in high dimensional ‘omics’ types of data. 

Max. 30 participants.

Summer School. Register here(link is external).

The course focusses on concepts and methods of mathematical modelling of infectious diseases. Applications to specific infectious diseases and intervention strategies will be discussed.

Register here(link is external).

The aim of this course is to introduce economic evaluation methodology and practice to persons unfamiliar with economic thinking in a healthcare and prevention context. Participants will be introduced to the main approaches to economic evaluation, the measurement of costs and effects, including quality of life measurements, economic modeling, and uncertainty analyses. Participants will also learn to assess economic evaluations as published in the literature.

The course topics will be covered in interactive lectures, case studies and group discussions. In addition, aspects of economic modeling will be covered extensively with computer exercises, in which participants will learn how to develop basic and advanced cost-effectiveness models. Lectures and computer exercises will be given by staff from the Health Technology Assessment group of the Julius Center/UMC Utrecht.

Register here(link is external).

Even in well designed and conducted epidemiological studies, data will be missing. This may include missing observations of the exposure and under study, confounders, or the outcome.

Possible mechanisms for data being missing will be discussed, as well as their potential impact in terms of bias. Focus will be on methods t handle missing data. Examples and exercises will come from various epidemiological studies, including diagnostic, prognostic, etiologic, and therapeutic studies.

Register here(link is external).

In the biosciences, response variables are often observed more than once per individual. This enables the researcher to study the development of the variable of interest within individuals, thereby eliminating the variation among individuals, and thus increasing the power of the design. However, since observations on the same individual are almost always correlated, special methods are needed to deal with this dependence.

Another way in which data can be dependent is when there is a hierarchical (multilevel) structure in your data, e.g. patients within hospitals, horses within farms, pupils within classrooms, etc.

Mixed models are one way of analyzing this kind of data. This statistical technique allows for the dependency of measurements in hierarchically structured data, and separately examines the effects of variables at different levels. An important part of the course will be about the use (and theory) of linear mixed effects models (LME’s).

Starting with analysis of summary statistics on each individual's observations, this course will lead you to more advanced methods for analyzing multilevel and longitudinal data. Similarities between longitudinal data analysis and multilevel analysis will be clarified. The course will focus primarily on continuous outcome variables, but attention will also be paid to dichotomous and count data.

Max. 60 participants. 

Register here(link is external).

This course provides statistical methods to study the association between (multiple) determinants and the occurrence of an outcome event. The course starts with an introduction to likelihood theory, using simple examples and a minimum of mathematics. Next, the most important regression models used in medical research are introduced. Topics are: maximum-likelihood methods, logistic regression, model validation and regression diagnostics, Poisson regression, and analysis of `event-history´ data, including an extensive discussion of the Cox proportional hazards regression model. Also, the basic principles of longitudinal data analysis are taught.

Summer School. Register here(link is external).

Max. 40 participants.

Register here(link is external).

The rapid growth of advanced molecular methods has revolutionized our understanding of epidemiology of infectious diseases. This course will introduce you to basic molecular typing tools, but also to next-generation sequencing and will illustrate applications of these tools in epidemiological studies. In this course, you will work with whole genome sequences, learn about sequence alignment and construct phylogenies. You will get an introduction to coalescent theory and see examples of the use of molecular epidemiology in outbreak analyses. Examples of genome-wide association studies and microbiome studies will be presented. The application of mathematical modelling of pathogen evolution and epidemiology will be discussed.

Max. 40 participants.

Summer School. Register here(link is external).

Summer School. Register here(link is external).

Register here(link is external).

Research training starts with the formulation of a research question and the design of a study. Research proposals are presented and discussed in a seminar with fellow participants, PhD students and senior staff members. In the second year students present a poster at the seminar.

Register here(link is external).

Prognosis is a key concept in patient care. The methodology of prognostic research is however relatively underdeveloped. This is in contrast to its growing importance in clinical medicine. In the course, principles and methods of non-experimental prognostic research will be discussed. In lectures, practical exercises and discussion of examples, the practice of prognostic research in a clinical setting is addressed. Emphasis will be on design and statistical analysis of prognostic studies, construction and estimation of prediction rules and approaches to validation and generalization of research results. Problems with small datasets will be extensively discussed.

Max. 60 participants. 

Register here(link is external).

Over the past decades, we have seen huge improvements in medical imaging technology. S ystematic evaluation of the quality and reproducibility of new imaging techniques is crucial to allow large scale implementation. This one week interactive course will focus on the many aspects of imaging evaluation, including technical development, visual assessment and optimisation of image quality, and intra and inter observer reproducibility. At the end of the week, students will be able to design, analyse and report imaging evaluation and reproducibility studies according to international guidelines.

Max. 30 participants. 

Register here(link is external).

As an epidemiologist you have to be able to reflect on social and ethical responsibilities linked to the application of your knowledge and judgements. Both in the design and conduct of research, as well as in the discussion, interpretation, and communication of research results, ethical considerations always play a role. The course aims to introduce you to theory, logical reasoning, and case studies, in the ethics of experimentation on human subjects, international research, and research on children and other vulnerable populations.
Also the role of epidemiological research within society is discussed. In particular you will be asked to formulate your personal view and ambitions within the field.

Max. 70 participants. 

Register here(link is external).

In this course the principles and practice of cohort, case-control and cross-sectional studies are taught. Design, data collection and outcome measures are discussed, as well as the major advantages and disadvantages of the different study designs. Emphasis is on the application of study design in etiologic research. The course focuses on the more classical approach but also addresses modern concepts and design options, such as case-cohort designs. Various study designs are discussed, with emphasis on issues of validity.

Max. 70 participants. 

Register here(link is external).

In this course you will learn the "state-of-the-art" in veterinary epidemiology. the course will focus on those aspects that are specific for epidemiology in animal health, but these concepts are relevant also in many other situations.

For instance, structured polulations (e.g. individuals grouped by herd, farm or pen) are common in animal health epidemiology, but also not uncommon in human epidemiology (e.g. nursing homes). You will learn to apply epidemiological and statistical methods, specific for structured populations during hands-on computer practical and lectures.

Max. 30 participants. 

Register here(link is external).

Survival data, or more generally, time-to-event data (where the “event” can be death, disease, recovery, relapse or another outcome), is frequently encountered in epidemiologic studies. Censoring is a problem characteristic to most survival data, and requires special data analytic techniques.

This course will give an introduction to survival analysis and cover many of the types of survival data and analysis techniques regularly encountered in epidemiologic research. The necessary statistical theory will be presented, but the course will focus on practical examples, with an emphasis on matching data analysis to the research question at hand. Lab sessions will give students the opportunity to apply the theory to real datasets.

Max. 40 participants. 

Register here(link is external).

The number of primary studies evaluating prognostic factors and models is rising. Critically summarizing and analyzing the evidence form prognostic studies in a systematic review and meta analysis, respectively,  is beneficial for health care professionals seeking the best evidence. Reviews of prognostic studies are more challenging because of more variation in questions & designs, specific sources of bias & variation, and more complex statistical models, as compared to e.g. randomized therapeutic intervention trials . Several advances regarding the design, critical appraisal and statistical analysis in systematic reviews of prognostic studies, have recently been made. In this course we discuss and practice how to define your review questions, how to critically assess the methodological quality of primary prognostic studies, and which statistical methods to use for meta-analyses of the results of primary prognostic studies. The course consists of plenary presentations, small-group discussions, and computer exercises.

Max. 40 participants. 

Register here(link is external).

The number of primary studies evaluating diagnostic tests is rising. Critically summarizing such studies in a systematic review is beneficial for health care professionals seeking the best evidence about the use of diagnostic tests. Reviews of diagnostic studies are more challenging because of more variation in questions & designs, specific sources of bias & variation, and the need to use more complex statistical approaches to meta-analysis. Several advances have recently been made in the methods to perform such reviews. In this course we discuss and practice the methods to assess the methodological quality of primary diagnostic test accuracy studies (QUADAS-2 instrument), the statistical models to meta-analyze the paired measures of test accuracy (bivariate meta-regression model of sensitivity and specificity), and how to critically read and interpret the findings of systematic review of diagnostic studies. The course consists of plenary presentations, small-group discussions, and computer exercises using the statistical software package R.

Max. 40 participants. 

Register here(link is external).

Systematic reviews and meta-analyses are an important cornerstone of contemporary evidence-based medicine. The large majority summarize published aggregate data, but it is increasingly common that individual participant data (IPD) are obtained from primary studies. As a result, new opportunities arise and more advanced statistical methods are needed to properly analyze the available data. In this course, we discuss how a meta-analysis involving IPD may help to identify sources of heterogeneous treatment effects, to investigate the accuracy of diagnostic tests, to develop clinical prediction models and to externally validate such models. We place particular emphasis on statistical methods for dealing with between-study heterogeneity, and discuss how to interpret corresponding results. The course consists of plenary presentations, small-group discussions, reading assignments, and computer exercises.

Max. 40 participants. 

Register here(link is external).

Meta-Analysis is the statistical approach to synthesis of the results from a series of studies. During this course we will present and discuss the rational and use of meta-analysis. We will discuss the strengths and limitations, and provide step-by-step guidance on how to perform a meta-analysis based on examples that either has provoked discussion on their logic and methods, or that have challenged conventional beliefs in medicine and biomedical sciences.
Logic and developments on particular approaches (e.g. model selection, individual patient data meta-analyses), and controversies in meta-analysis will be discussed during interactive tutorials (e.g. dealing with heterogeneity and when to refrain from meta-analysis).
Participants will learn how to conduct a meta-analysis. They will get hands-on experience on different aspects of the design and conduct of meta-analysis, including computer practicals using Excel, Comprehensive Meta-Analysis (CMA), STATA and MIX. By the end of the course, participants should be able to conduct a meta-analysis.
Participants gain access to the online materials the week before the course. Participants are encouraged to bring their laptop.

Max. 60 participants. 

Register here.

Diagnostic research in the past focused particularly on estimating the sensitivity and specificity of individual diagnostic tests. This course will demonstrate that this so called 'test research'  is not necessarily the same as diagnostic research. Furthermore, we will widen the horizon by proposing modern methods of diagnostic research and data analysis in which a patient's test result can and should be considered in the context of other patient characteristics or test results. These methods enable 1. direct estimation of individual probabilities of disease presence based on all diagnostic information and 2. evaluation of the extent to which a particular diagnostic test has true added value in the clinical context. Also, conventional and advanced methods for systematic reiews of diagnostic tests will be presented.

Max. 60 participants. 

Register here.

This course will address two important topics in causal epidemiologic research, namely confounding and effect modification. These topics will be discussed in the context of both etiologic research and observational intervention research. Effect modification and confounding are difficult concepts to understand and often mixed up. In this course the theory as well as the practical side of these issues will be discussed.

Max. 60 participants. 

Register here.

Max. 20 participants. 

Summer School. Register here(link is external).

Max. 50 participants. 

Register here(link is external).

The objective of the course is to provide the participant with insight in the principles and important issues of cardiovascular disease epidemiology. Topics that will be covered are:

• Atherosclerosis, the underlying pathology for the most common cardiovascular diseases;
• Risk factors for cardiovascular disease;
• Worldwide trends in cardiovascular disease morbidity and mortality;

In addition, there will be several key lectures given by invited speakers from both inside and outside the UMC Utrecht. During these lectures the latest developments in CVD epidemiology will be presented. Topics in key lectures may include sex differences in CVD, the importance of genes and environmental factors in CVD.
Interactive teaching is key in this course. Apart from active participation during the lectures, the participant will be assigned to tasks: First, an individual assignment about cvd research in 2030 has to be made and second particpants have to defend a proposition in a debate. This will be a group assignment.

Register here(link is external).

This course covers the basic applications of biostatistics in the analysis of medical research data.

Register here(link is external).

In clinical epidemiology, research is focused on questions of diagnosis, prognosis, treatment and etiology. To address these questions, several research options are available, including intervention trials and case-control studies using data obtained in a clinical setting.
In the course, the principles and practice of clinical epidemiology will be considered and examples from the literature will be worked out and discussed. The aim is to provide the participants with the knowledge to evaluate and judge applied clinical research and data analysis and give a sufficient scientific and methodological background to actively participate in clinical studies.

Topics are: principles of applied clinical research, study design and analysis of diagnostic and prognostic research, study design and analysis of comparative (clinical) experimental and non experimental studies.

Register here(link is external).

A clinical trial is an exceedingly important instrument in the assessment of treatment efficacy. With regard to clinical trials, the emphasis will be on methodological principles and on the clinical practice of therapeutic experiments. Furthermore, this course addresses the principles of studying the effects of drug treatments on the risks of unintended effects. The accent is on proper formulation of the research problem with a view to clinical and regulatory relevance of the study results, and on requirements for validity in non-experimental research.

The course program covers the principles of therapeutic research design, including design of study, design of data collection, design of data analysis, including some modelling techniques in the analysis to clinical trials, and the interpretation of its results. Finally the program covers the principles of drug risk assessment in the context of therapeutic research. Seminal lectures on trials and practical exercises are included in the program.

Register here(link is external).

Computational statistics concerns the development, implementation and study of computationally intensive statistical methods. Such methods are often used e.g. in the fields of data visualization, the analysis of large datasets, Monte Carlo simulation, resampling methods such as the bootstrap, permutational methods, Markov Chain Monte Carlo methods and various numerical methods of equation solving such as the EM algorithm and Newton-Raphson iteration. A very powerful tool to implement such methods is the R statistical programming language.

This course will present essential methods in computational statistics in a practical manner, using real-world datasets and statistical problems. Examples will include e.g. 1) evaluating and comparing the performance of different statistical techniques in a specific setting using simulation, 2) implementing complex methods such as an EM algorithm to fit a joint model, 3) implementing the bootstrap to obtain a standard error estimate which is not available in closed-form. We will also develop advanced R programming skills.

Register here(link is external).

Max. 20 participants. 

Register here(link is external).

Infectious diseases are an important cause of disease burden in animals, as well as humans. Infectious animal disease epidemiology is important in both a veterinary.

You will learn techniques and theory of veterinary epidemiology of animal infectious diseases, including mathematical modelling, design and analysis of infectious disease animal transmission experiments, infectious disease risk mapping, risk assessment and disease surveilllance.