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Informatie over MSc Courses for Exchange Students: Biology & Life Sciences
Hieronder staan het programma en de vakomschrijvingen van MSc Courses for Exchange Students: Biology & Life Sciences Klik op de naam van een vak in een schema om naar de omschrijving te gaan.
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| Periode | Type | Code | Naam | Taal | ECTS | Uren | |
|---|---|---|---|---|---|---|---|
| hele jaar | verplicht | MLAA01 | Animal and Human Experimentation | Engels | 5 | ||
| verplicht | MLBI1002 | GELIFES lectures | Engels | 2 | |||
| semester I a | verplicht | WMLS18002 | Biological Modelling and Model Analysis | Engels | 10 | ||
| verplicht | WMBE14003 | Biomaterials 2 | Engels | 5 | |||
| verplicht | WMBE17003 | Conventional Imaging Techniques and Ultrasound | Engels | 5 | |||
| verplicht | MLBMTLAB05 | Integrated Lab Course Biomaterials | Engels | 5 | |||
| verplicht | MLBMTGB05 | Interface Biology | Engels | 5 | |||
| verplicht | WNBIBEB08A | Introduction Science and Business | Engels | 10 | |||
| verplicht | WNBIBEB08B | Introduction Science and Policy | Engels | 10 | 40 | ||
| verplicht | WMBE17004 | Introduction to MATLAB Programming for BME | Engels | 5 | variabel | ||
| verplicht | WMLS18001 | Mathematics in the Life Sciences | Engels | 5 | |||
| verplicht | WMBE18005 | Microscopy and Imaging | Engels | 5 | |||
| verplicht | MLBB005 | Molecular Dynamics | Engels | 5 | 40 | ||
| verplicht | WMBE18004 | MRI | Engels | 5 | |||
| verplicht | WMBE14001 | Physics in Nuclear Medicine | Engels | 5 | 4 | ||
| verplicht | MLBMTROB05 | Recent developments in biomaterials | Engels | 5 | |||
| verplicht | MLBB010 | Tools and approaches of systems biology | Engels | 5 | |||
| semester I b | verplicht | WMLS13003 | Advanced Genetic Engineering | Engels | 5 | ||
| verplicht | WMBE18001 | Applied Medical Visualization | Engels | 5 | |||
| verplicht | MLGBB04 | Biocatalysis and Green Chemistry | Engels | 5 | |||
| verplicht | WMBE17002 | Biofilms | Engels | 5 | variabel | ||
| verplicht | MLBMTCG | Colloid and Interface Science | Engels | 5 | 4 | ||
| verplicht | WMBE17001 | Computed Tomography | Engels | 5 | |||
| verplicht | WMEV19001 | Ecology of sustainable farming | Engels | 5 | |||
| verplicht | WMBE14005 | Engineering and Biotribology | Engels | 5 | |||
| verplicht | WMLS15001 | Flyway Ecology (20/21) | Engels | 5 | |||
| verplicht | WMLS15003 | Marine Evolution | Engels | 5 | 40 | ||
| verplicht | MLBMTKFR | Medical Physics for Radiation Oncology | Engels | 5 | |||
| verplicht | WMLS15004 | Practical Modelling for Biologists | Engels | 5 | 40 | ||
| verplicht | WMLS15006 | Principles of Marine Conservation | Engels | 5 | |||
| verplicht | WMLS17003 | Programming C++ for Biologists | Engels | 5 | |||
| verplicht | WMBE14004 | Prosthetics and Orthotics | Engels | 5 | 4 | ||
| verplicht | MLBMTOK | Surface characterization | Engels | 5 | |||
| verplicht | MLBMTTER05 | Technology and the Ethics of Research | Engels | 5 | |||
| semester II | verplicht | MLBIE09 | Current Themes Seminar Series (Bio/EE/MB) | Engels | 2 | ||
| verplicht | MLMB01A | Meta-analyses in Ecology (20/21) | Engels | 5 | |||
| verplicht | WMLS09002 | Orientation on International Careers | Engels | 5 | |||
| semester II a | verplicht | WMBE13001 | Biomedical Instrumentation 2 | Engels | 5 | ||
| verplicht | MLBIE08C | Mathematical Models in Ecology and Evolution | Engels | 6 | |||
| verplicht | MLBMTPR05 | Multidisciplinary Project | Engels | 5 | |||
| verplicht | MLMB03 | Polar Ecosystems | Engels | 5 | |||
| verplicht | WMBE19001 | Statistical Methods for BME | Engels | 5 | |||
| semester II b | verplicht | MLBI0901 | Advanced Imaging techniques | Engels | 5 | ||
| verplicht | WMLS13004 | Advanced Light Microscopy | Engels | 5 | |||
| verplicht | MLBI0801 | Advanced self-organisation of social systems | Engels | 5 | |||
| verplicht | WMLS19002 | Advanced Statistics | Engels | 6 | |||
| Opmerkingen | o TERMS: In the Netherlands, the academic years are not only divided into semesters, but also in ‘terms’. Each semester consists of 2 terms. The 1st semester entails a term 1a and 1b (Term 1a is the 1st half of the 1st semester. Term 1b, the 2nd half of the 1st semester). Term 2a (or IIa) stands for the 1st half of the 2nd semester and 2b (or IIb) for the 2nd half of the 2nd semester. | ||||||
| 1 | Advanced Genetic Engineering | WMLS13003 | |||||||||||||||||||||||||||
| The emphasis will be on the practical aspects of genetic engineering of novel circuitries and on the principles of Synthetic Biology, both in silico and in the lab. In principle, the students will work in pairs on a research project in the practical part. The students will avail of- and study a number of bacterial strains with earlier developed DNA-biobricks (also from iGEM collections). Novel circuitries will be designed and engineered using Gram-positive or Gram-negative organisms as hosts. Modeling efforts will support the design. The engineered circuits will be characterized using various statistics-, bioinformatics and visualization packages, and functionality will be tested experimentally (e.g. by fluorescence microscopy or enzymatic assays). In this course, theory and practicals will be combined to give an in-depth view of current (high-throughput) genetic engineering approaches, gene regulatory mechanisms and -networks related to microbial physiology-Advanced genetic engineering: this includes use of Biobricks, Gibson assembly, use of BACs and YACs, toolboxes, gene integration, complex genetic circuitries (natural and synthetic): bistability, toggle switches, oscillations, feed-back mechanisms. | |||||||||||||||||||||||||||||
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| 2 | Advanced Imaging techniques | MLBI0901 | |||||||||||||||||||||||||||
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| 3 | Advanced Light Microscopy | WMLS13004 | |||||||||||||||||||||||||||
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| 4 | Advanced self-organisation of social systems | MLBI0801 | |||||||||||||||||||||||||||
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| 5 | Advanced Statistics | WMLS19002 | |||||||||||||||||||||||||||
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| 6 | Animal and Human Experimentation | MLAA01 | |||||||||||||||||||||||||||
| This course is in transition to a completely new e-learning format in 2020. Please be prepared for possible change during the academic year. The learning objectives, content and judgement will be very similar, but the format is changed to learning via videos, quizzes, and assignments. Enrolling in this course is only finalized once you will have completed following your first instruction in NESTOR. Thereafter, selected course participants will work within a google classroom environment, where more detailed information will be provided. The aim of the course is to prepare students starting a master research project in which they participate in animal or human experimentation, with respect to methodological, practical and ethical aspects. At the end the students are prepared to carry out the masterproject, under supervision of and guided by the CCD or METC permit holder. The course has a blended classroom format with a limited contact hours. The students complete an online portfolio after practical instructions in their master project, and conduct the theoretical part as a homework assignment. They will also participate in a tour through the animal/human facility to learn about practical procedures while performing their study and the people involved, and attend a contact hour with an interactive lecture when topics can be discussed. The theoretical part consists of 6 modules containing information on (1) Ethics and researcher integrity in animal and human experimentation, (2) Rules & Regulations in animal and human experimentation, (3) Research question, experimental and statistical design, (4) Choice of experimental model and subjects, (5) Animal experimentation in practice, and (6) Human experimentation in practice. By in-depth reading of scientific papers, looking up content on the internet and by self-reflection, students will learn about scientific, practical and societal aspects of working with animals and/or humans during their masterproject. | |||||||||||||||||||||||||||||
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| 7 | Applied Medical Visualization | WMBE18001 | |||||||||||||||||||||||||||
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| 8 | Biocatalysis and Green Chemistry | MLGBB04 | |||||||||||||||||||||||||||
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| 9 | Biofilms | WMBE17002 | |||||||||||||||||||||||||||
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| 10 | Biological Modelling and Model Analysis | WMLS18002 | |||||||||||||||||||||||||||
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| 11 | Biomaterials 2 | WMBE14003 | |||||||||||||||||||||||||||
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| 12 | Biomedical Instrumentation 2 | WMBE13001 | |||||||||||||||||||||||||||
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| 13 | Colloid and Interface Science | MLBMTCG | |||||||||||||||||||||||||||
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| 14 | Computed Tomography | WMBE17001 | |||||||||||||||||||||||||||
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| 15 | Conventional Imaging Techniques and Ultrasound | WMBE17003 | |||||||||||||||||||||||||||
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| 16 | Current Themes Seminar Series (Bio/EE/MB) | MLBIE09 | |||||||||||||||||||||||||||
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| 17 | Ecology of sustainable farming | WMEV19001 | |||||||||||||||||||||||||||
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| 18 | Engineering and Biotribology | WMBE14005 | |||||||||||||||||||||||||||
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| 19 | Flyway Ecology (20/21) | WMLS15001 | |||||||||||||||||||||||||||
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| 20 | GELIFES lectures | MLBI1002 | |||||||||||||||||||||||||||
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| 21 | Integrated Lab Course Biomaterials | MLBMTLAB05 | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 22 | Interface Biology | MLBMTGB05 | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 23 | Introduction Science and Business | WNBIBEB08A | |||||||||||||||||||||||||||
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| 24 | Introduction Science and Policy | WNBIBEB08B | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 25 | Introduction to MATLAB Programming for BME | WMBE17004 | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 26 | Marine Evolution | WMLS15003 | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 27 | Mathematical Models in Ecology and Evolution | MLBIE08C | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 28 | Mathematics in the Life Sciences | WMLS18001 | |||||||||||||||||||||||||||
| The course will: - train basic mathematical skills, such as differentiation and integration; - introduce students to important mathematical concepts and methods, such as complex numbers, linear algebra, multivariate analysis, and linearization techniques; - provide insight into the use and interpretation of dynamical models in the life sciences; - expose students to important classes of example models in the life sciences; - teach students how to investigate dynamical models with analytical and numerical methods; - expose students to more advanced concepts and methods, such as chaotic attractors and bifurcation analysis; - teach students how to solve mathematical problems with the help of technical computing software (Mathematica). The first week of the course will focus on mathematical key concepts (such as differentiation, integration, Taylor expansion) and on the analysis of one-dimensional dynamical systems (single ordinary differential equations (ODEs) and single recurrence equations). Students will learn how to solve these systems either analytically or numerically, both with pencil and paper and with a programme like Mathematica, and to perform an equilibrium and stability analysis. Students will also be exposed to bifurcation analysis, catastrophes, and chaotic attractors. In the second week, complex numbers and concepts of linear algebra (eigenvalues and eigenvectors) will be introduced. Students will learn the basics of multivariate analysis, including multivariate optimization (Hessian). These techniques will allow them to analyse simple stochastic systems, like Markov processes. Students also learn how to analyse 2nd_ order ODEs and recurrence equations. The third week is devoted to systems of ODEs and recurrence equations. Students learn how to solve linear systems analytically, how to solve non-linear systems numerically, and how to conduct a qualitative analysis of a multidimensional dynamical system (equilibrium and stability analysis). | |||||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 29 | Medical Physics for Radiation Oncology | MLBMTKFR | |||||||||||||||||||||||||||
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| terug naar boven | |||||||||||||||||||||||||||||
| 30 | Meta-analyses in Ecology (20/21) | MLMB01A | |||||||||||||||||||||||||||
| Generalization of ecological research by the synthesis of experiments and data from the literature has proven to be an important modern complement to empirical ecological research. Instead of focusing on an indefinite number of idiosyncratic exceptions meta-analysis emphasizes general insights and promotes common ecological understanding. Understanding the function of biodiversity is an emerging ecological topic related to ecosystem functioning. It facilitates predicting consequences of biodiversity loss for ecosystem services by the global biodiversity crisis. The course will: 1) give an overview on the importance of species diversity and species functional traits for the function of important community properties. 2) teach to use different tools in ecological meta-analysis. 3) perform a meta-analysis, including tests of own hypothesis, either using provided datasets of experiments testing the function of biodiversity for ecosystem performance (B~F experiments), or using own data collected from recent literature. The course is given together with the University of Oldenburg, and is arranged around three workshops. The first workshop (in Wilhelmshaven, Germany) contains theoretical sections on biodiversity. The second workshop is on tools used to extract, handle and analyze large data sets using meta-analyses. There will be a strong focus on recent literature and the students are expected to analyze this literature for new exciting questions. In the third workshop (in Groningen, The Netherlands) the results will be presented at a mini-symposium. The course is run over ca. 8 weeks during which the main effort will be to produce your own ecological meta-analysis! Thus, the course can be run in parallel with other master projects | |||||||||||||||||||||||||||||
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| 31 | Microscopy and Imaging | WMBE18005 | |||||||||||||||||||||||||||
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| 32 | Molecular Dynamics | MLBB005 | |||||||||||||||||||||||||||
| Together with experiment and theory, computational modeling is one of the three pillars of modern science. In chemistry as well as in life sciences, modeling of the interactions between molecules is essential to understand the emerging behavior of complex systems. In particular the Molecular Dynamics (MD) simulation technique provides a detailed view of the behavior of molecules in space and time, at a resolution that cannot be attained by any single experimental technique. In a series of lectures, the underlying theory (statistical thermodynamics), the diversity of molecular models (atomistic, coarsegrained), and numerical techniques (integration of Newton's equations of motion) used in MD simulations will be discussed. Applications of the technique will be shown, with a focus on simulation of biomolecular processes. An important part of the course is hands-on experience using the GROMACS modeling software in a series of tutorials and practicals covering the basics of the techniques and selected applications, e.g. self-assembly of lipids in water or sampling the conformational space of proteins. | |||||||||||||||||||||||||||||
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| 33 | MRI | WMBE18004 | |||||||||||||||||||||||||||
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| 34 | Multidisciplinary Project | MLBMTPR05 | |||||||||||||||||||||||||||
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| 35 | Orientation on International Careers | WMLS09002 | |||||||||||||||||||||||||||
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| 36 | Physics in Nuclear Medicine | WMBE14001 | |||||||||||||||||||||||||||
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| 37 | Polar Ecosystems | MLMB03 | |||||||||||||||||||||||||||
| The course is based on a series of lectures (22) and a reading assignment. Lectures will be given by internal (ESRIG, Arctic Centre) as well as external (NIOZ) polar experts. Topics covered are polar climatology, marine and terrestrial polar habitats, key species, effects of climate change from species to ecosystem level, and other human impacts. The second part of the course consists of a reading assignment, followed by presentations. A set of key scientific papers will be handed out to small groups of students (max 3 per group), covering as much scientific disciplines as possible. The students will need to understand, reproduce, summarize, evaluate and discuss the result and implications of the papers during a symposium, where the reading assignments will be presented. The course will be evaluated by a written examination. Examination material includes syllabus material from the lectures as well as a selection of key scientific papers. | |||||||||||||||||||||||||||||
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| 38 | Practical Modelling for Biologists | WMLS15004 | |||||||||||||||||||||||||||
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| 39 | Principles of Marine Conservation | WMLS15006 | |||||||||||||||||||||||||||
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| 40 | Programming C++ for Biologists | WMLS17003 | |||||||||||||||||||||||||||
| This course, which is specifically designed for biology students, teaches the participants how to develop software in the programming language C++. Emphasis is given to the implementation of biological models, using individual-based simulations and various numerical methods for dynamical systems analysis. Students are able to tailor the contents of the course to their own level of proficiency. For students with no prior programming experience, the course offers an introduction to the essentials of the C++ programming language, including: • Procedural programming: data types, operators, program flow and functions • The Standard Template Library • Data input, generation of output including statistics like mean and standard deviation • Numerical simulation techniques for biological models More experienced programmers (including those who followed the BSc level course WBLS16002) can instead focus on advanced topics, such as: • Program design, algorithms and debugging • Pointers and memory allocation • Object-oriented programming • Pseudo-random numbers and stochastic simulations The course consists of two parts: during the first three weeks (5 ECTS), students extend their programming skills by learning a new element of the programming language each day, and practise its application in programming exercises. The final three weeks of the course (5 ECTS) are devoted to a programming project. Here, students work on a biological research question of their choice and design and implement a simulation algorithm from scratch. They also learn how to systematically collect simulation data, and to present their results in an oral presentation, with associated annotated program code and documentation. Students may choose to omit the final project and receive a grade for a 5 ECTS course (MLAA05) after completing the first half of the program, or may work independently on their programming project at a suitable later time. The course is also available as a selfstudy course. | |||||||||||||||||||||||||||||
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| 41 | Prosthetics and Orthotics | WMBE14004 | |||||||||||||||||||||||||||
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| 42 | Recent developments in biomaterials | MLBMTROB05 | |||||||||||||||||||||||||||
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| 43 | Statistical Methods for BME | WMBE19001 | |||||||||||||||||||||||||||
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| 44 | Surface characterization | MLBMTOK | |||||||||||||||||||||||||||
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| 45 | Technology and the Ethics of Research | MLBMTTER05 | |||||||||||||||||||||||||||
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| 46 | Tools and approaches of systems biology | MLBB010 | |||||||||||||||||||||||||||
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