Molecular genetic research techniques

In deze voornamelijk praktische cursus leren jullie hoe je experimenteel processen in levende bacteriën, gisten, planten en zoogdiercellen kunt bestuderen, en de moleculair-genetische technieken die hiervoor worden toegepast. De technieken die jullie gaan leren en toepassen variëren van basale tot geavanceerde recombinante DNA-technieken, zoals: overdracht van genetisch materiaal tussen bacteriën, genetische mapping in planten, yeast-2-hybrid en genetische complementatie in gist, eiwitisolatie uit zoogdiercellen, Western blotting, immunocytochemie en confocale lasermicroscopie.
Buiten de praktijk leren jullie uitgebreid over de theoretische achtergrond achter de verschillende toepassingen, zodat jullie een beter beeld krijgen van welke techniek waarvoor het beste toepasbaar is.
Om je goed voor te bereiden op de practica krijg je iedere week hoorcolleges en zelfstudie-opdrachten. Tijdens de practica leren jullie ook nauwkeurig labnotities bij te houden en op basis daarvan een labjournaal of labverslag te schrijven. Dit is essentieel om experimenten reproduceerbaar te maken. Tijdens de nabesprekingen van de practica en de data-analysecolleges leer je hoe je de data die je tijdens het practicum hebt gegenereerd kwalitatief en kwantitatief analyseert.
Verder kun je in deze cursus je ‘Veilige Microbiologische Technieken’ (VMT) diploma behalen, een essentiële kwalificatie voor iedereen die in een laboratorium moleculair genetisch gaat werken.

Program/Minor

Learning Outcomes

Beschik je over uitgebreide moleculair-genetische kennis; Begrijp je moderne moleculair-genetische technieken en kun je deze toepassen; Ben je in staat om onderzoek in het lab uit te voeren en zorgvuldig te documenteren; Kun je de tijdens het practicum verkregen data kwalitatief en kwantitatief analyseren en interpreteren, met behulp van geschikte software zoals ‘R’ of ‘Fiji’; Kun je moleculair-genetische vraagstukken zelfstandig(er) benaderen en oplossen met de opgedane kennis en vaardigheden; Begrijp en pas je een systematische benadering toe bij het oplossen van biologische problemen en onderzoeksvragen; Heb je inzicht in complexe biologische systemen en kun je deze analyseren en hanteren; Ben je beter in staat om primaire wetenschappelijke artikelen (beter) te interpreteren met behulp van je opgedane kennis en vaardigheden; Een onderzoekcyclus begrijpen en in groepsverband uitvoeren, documenteren en analyseren met ‘R’; Browsers en databases gebruiken om informatie over genen te vinden en om DNA-sequenties te analyseren; Kritisch denken, eigene resultaten kritisch kunnen bediscussiëren en kritisch feedback kunnen geven en ontvangen

Prerequisites

Aantoonbare beheersing van de kennis van de cursussen Moleculaire biologie en Genomica op niveau 1 van de bachelor opleiding Biologie of kennis die daarmee vergelijkbaar is. B-B2MGOT14 is equivalent aan SK-B2MBBT en kan niet door MLS-studenten worden gevolgd. B-B2MGOT14 kan niet gevolgd worden door studenten die B-B3MCR18 succesvol hebben afgerond.

Details

Institution: UU

Period: Period 2

Level: Intermediate

EC: 7.5 ec

Molecular Genetics and Gene Technology

Het vak Moleculaire Genetica en Gentechnologie (MGG) bestaat uit een theoretisch deel (hoorcolleges en opdrachten) en een bijpassend praktisch deel.

Bij het theoretische deel komen diverse aspecten van de Moleculaire Genetica ter sprake: DNA herstel mechanismen; DNA structuur (eu- en heterochromatine, DNA -en histon modificaties als essentiële onderdelen van epigenetica, mobiele DNA elementen); RNA (silencing, splicing, editing, stabiliteit, gebruik van RNA varianten in therapie); Eiwit (ribosomen, werking antibiotica, heatshock eiwit therapie); Maken en mogelijke toepassing van iPSC en organoïden; Lipiden in het bijzonder de sfingolipiden (opbouw, context en functioneel testen in cellulaire, of dierlijke systemen); Recente DNA technologie ontwikkelingen (CRISPR-CAS editing, virale systemen, therapeutische toepassing, onder ander AAV en maken knock out modellen).

Het practicum bouwt voort op de colleges en een aantal van de daar behandelde recombinant-DNA-technieken zal aan bod komen, waaronder PCR, “knippen en plakken” van DNA, Gibson assembly, kweken en transformeren van colibacteriën, plaatsgerichte nucleotiden veranderingen m.b.v. CRISPR-CAS, gelelektroforese van DNA en eiwitten, western blotting, in vivo detectie d.m.v. fluorescentie, sequentie-analyse, zoeken in DNA-databanken.

Program/Minor

Learning Outcomes

Inzicht krijgen in een aantal processen en verschijnselen in de cel op het niveau van chromosomale structuur en organisatie, genexpressie en posttranscriptionele en (post)translationele regulatie. Inzicht krijgen in de achtergronden en technieken van de recombinant DNA-technologie en het kunnen toepassen van deze kennis op probleemstellingen uit de praktijk. Het leren lezen en presenteren van complexe wetenschappelijke artikelen; Gentechnologische technieken kunnen doorgronden en toepassen; Gentechnologische experimenten nauwkeurig kunnen uitvoeren en de resultaten zorgvuldig kunnen waarnemen en vastleggen; Stof behandeld in de colleges kunnen toepassen bij de interpretatie van experimentele resultaten; Uitvoering, resultaten en interpretatie van onderzoek schriftelijk kunnen vastleggen op academisch niveau, gestructureerd als een wetenschappelijke publicatie en begrijpelijk voor een niet-ingewijde vakgenoot

Prerequisites

Life Sciences

Details

Institution: TU Delft

Period: Period 4

Level: Intermediate

EC: 9 ec

Molecular Plant Microbe Interactions

The aim of this course is to understand how the immune system of plants functions, how plants and beneficial or pathogenic microbes interact with each other, and what the determinants are for their success in these different interactions. In the course several integration levels of plant-microbe (and -insect) interactions are discussed: from genes, signal molecules, defense products, whole organisms, to (microbial) population effects.
In the first half of the course, lectures and tutorials convey the theoretical underpinning of plant-microbe/insect interactions. Next to that, students carry out experiments in the laboratory. In the laboratory practicals the students perform plant disease tests with microbes and insects and measure molecular reactions to understand the complexity of the plant-microbe interactions.
In the second half of the course, students follow computer practicals in which they learn how to analyze genomic and transcriptomic data using R. The course is concluded by a key stone assignment in which students formulate a research question and experimental approach, based on their personal interest, in an in-depth MSc research project proposal.

Program/Minor

Learning Outcomes

Describe the characteristics of various interactions of the plant with beneficial and harmful microbes and insects; Describe the most important cellular and molecular mechanisms of attraction or defense between the different interactors (plant-microbe/insect and vice versa); Explain how defense and virulence mechanisms have developed during evolution, and understand the basic principles of the plant immune system; Describe the main regulation mechanisms by plant defense hormones and how these are influenced by multiple stress stimuli; Understand the functional relationship of the plant with its microbiome; Understand how bioinformatic analyses of high-throughput genomics data (at transcriptome and metagenome levels) can elucidate plant-microbe relationships; Define opportunities to translate fundamental scientific findings into the design of (disease) resistant crops; Explain how the above learning objectives can be studied experimentally; Critically interpret (own) experimental data using theoretical knowledge; Conduct a literature review, formulate a research question, devise scientific experiments, perform experiments, and present research plans and/or results (oral and written)

Prerequisites

Compulsory for Biology students level 2: “Moleculair Genetische Onderzoeks Technieken (MGOT)” (can be taken alongside this course, in the same period). Recommended: “Microbiele interacties (former course)”, “Microbiologie” or “Host-microbe interactions” or “Plantenfysiologie en -ontwikkeling” or “Planten in context”. M(B)LS students who followed Molecular Biology and Biochemical Techniques (MBBT) or an equivalent can also enter this course.

Details

Institution: UU

Period: Period 2

Level: Advanced

EC: 7.5 ec

Molecular Systems Biology

Nowadays increasing numbers of complete genomic sequences are available and methods have been developed to study system wide gene expression, protein abundances and interactions and metabolite formation. Systems biology integrates the results of the different omics techniques in order to understand how they work together by using dedicated analysis and visualisation techniques (e.g. machine learning, networks). These methods allow the extraction of relevant information for elucidating the function of genes, transcripts, proteins and metabolites, to signify interactions between these molecules, and to study the underlying regulatory mechanisms. The course is modular and focuses on data generation, mining, analysis, and data integration and visualisation.

Program/Minor

Learning Outcomes

Explain variation control and experimental design used in the generation of omics datasets; Apply univariate and multivariate statistical and machine learning (ML) methods to analyse omics data; Compare these statistical methods with each other and explain which method is applied for which type of biological question; Interpret mass spectrometry datasets of proteins; Construct, enhance and mine biological networks of molecular interactions from omics data; Analyse network topology using precise mathematical definitions, R and Cytoscape; Construct protein classes based upon network properties; Evaluate 'omics' information with respect to the biological questions

Prerequisites

The course accepts students with a biological background. Preferably the student will have some experience with bioinformatics tools and statistics: the courses Computational Biology (SSB34306 ) and Advanced statistics (MAT20306) are highly recommended.

Details

Institution: WUR

Period: Period 3

Level: Advanced

EC: 6 ec

Natuurlijk in gesprek (communicatie)

Life-long learning: Focused on effective collaboration within large projects and diverse groups

Details

Institution: HVHL

EC: LLO ec

Neurale Netwerken

The Neural Networks course introduces second-year BSc Artificial Intelligence students to the fundamental principles and architectures underlying modern neural computation. The course begins with foundational concepts such as perceptrons, multi-layer perceptrons, and the backpropagation algorithm. It then develops the student’s understanding of deep learning architectures including convolutional neural networks, recurrent neural networks, and transformers. In the final weeks, the course explores biologically inspired models such as Hebbian learning, Hopfield networks, and Boltzmann Machines. Students will gain both theoretical insight and practical experience through lectures, hands-on sessions, and supervised training exercises, preparing them for more advanced AI coursework and research.

This course introduces the foundational principles and architectures of neural networks, from simple perceptrons to advanced deep learning systems. Students begin by studying historical developments and core concepts such as activation functions, layers, and the backpropagation algorithm. The course covers optimization and regularization techniques essential for training neural networks effectively. Subsequently, it introduces convolutional neural networks (CNNs), residual networks, recurrent neural networks (RNNs), and transformer architectures. In the final weeks, biologically inspired models such as the Hebbian learning rule, Hopfield networks, and Boltzmann machines are presented. The course balances theoretical understanding with good practices in training and evaluating networks, preparing students for both academic research and real-world applications in AI.

Program/Minor

Learning Outcomes

The student knows what is a perceptron, an multi-layer perceptron (MLP); The student knows what is an nonlinear activation function, neural network layers and modules, and neural network parameters; The student knows the backpropagation algorithm; The student knows optimization and regularization algorithms for training the neural network; The student knows convolutional neural network (CNN), a deep neural network (DNN), and transformer architectures; The student knows recurrrent neural network; The student knows Hebbian learning rule, Hopfield networks, Boltzmann Machines

Prerequisites

Basic knowledge of linear algebra (vectors, matrices); Basic probability and statistics; Introduction to AI or Machine Learning courses are recommended but not mandatory

Details

Institution: UvA

Period: Period 4

Level: Intermediate

EC: 6 ec

New Trends in Plant Breeding

This course aims at sparking interest in a wide array of topics, which can be useful for a career in plant breeding industry or in science. Subjects treated are at a higher integration level, not only taking into account plant breeding aspects, but regarding all aspects involved, such as environmental issues, products and chain issues, climate change, technical possibilities, limiting resources and participatory approaches. Subjects treated include new trends and technologies in plant breeding, climate resilience, new crops, breeding for low-input cropping systems, breeding for symbiosis between plants and micro-organisms, automatic phenotyping, and breeding for alternative cropping systems such as strip cropping, urban agriculture and vertical farming.

Program/Minor

Learning Outcomes

Evaluate the challenges of urban agriculture from the breeding perspective; Assess morphological and physiological components relevant for the breeding of climate resilient plants; Design breeding programs on alternative cropping systems, such as mixed cropping systems, low-input cropping systems and vertical farming systems; Evaluate breeding possibilities in new crops; Evaluate novel breeding techniques; Evaluate the usefulness for plant breeding of different automated phenotyping techniques

Prerequisites

Principles of Plant Breeding (online) or Plant Breeding (on-campus); Breeding for Quality (online) and Breeding for Abiotic Stress Tolerance (online) or Breeding for Stress Tolerance and Quality (on-campus); Breeding for Resistance (online) or another course dealing with plant-pathogen interactions; Plant Biotechnology (online) or Plant Biotechnology (on-campus); Markers in Quantitative Genetics and Plant Breeding (online) or Pre-Breeding (on-campus).

Details

Institution: WUR

Period: Period 6

Level: Advanced

EC: 3 ec

Perspectives on Information and Society

The main aim of the course is to critically reflect on concepts central to Information Studies in terms of assumptions, limitations, and social and ethical implications. As information is the central notion of Information Studies we start with information. We approach information by using hermeneutics; this perspective highlights the characteristics of human understanding and is compared with an engineering perspective on information. Secondly we highlight current critique related to the use of data and algorithms in society; from this critical perspective we explore opportunities to improve the design of algorithms and information systems. Thirdly we explore the fundamentals of management and relate these to digitalization of society. We identify challenges for management and control from a traditional scientific management approach and from the perspective of Complex Adaptive Systems. The last topic is power. We identify characteristics of power both from a static and dynamic perspective and explore related challenges for IS-topics.

The course is divided in two parts. The focus during the first part is on understanding the different perspectives described above. In the second part, students are challenged to apply, explore and discuss the different perspectives in relation to specific IS-topics like design, implementation and living with numbers in a digital society. A variety of articles -incl. practical cases- is used to support this exploration.

If applicable, students are explicitly invited to share their work experience during the course, esp. students with jobs in the IS-field. These real-life situations can then be explored and assessed from the perspectives under discussion.

Program/Minor

Learning Outcomes

The student is able to identify and explain two perspectives on information i.e. representational knowing and hermeneutic understanding; The student is able to identify and explain current critique related to the use of data and algorithms in society; The student is able to contrast management as scientific management and as manus management; The student is able to identify and explain a static and dynamic perspective of power; The student is able to develop and formulate implications of different perspectives for several IS-related topics; The student is able to critically assess the different perspectives described above.

Details

Institution: UvA

Period: Period 4

Level: Master

EC: 6 ec

Perspectives on Sustainability Transitions in Agriculture

Sustainability transitions in agriculture seem inescapable. The nitrogen crisis, climate change, and diminishing biodiversity demand that governmental actors, nature conservation organizations, together with farmers, retailers, industry, academics and others develop alternatives to the dominant forms of agriculture. A protein transition, circular agriculture, nature inclusive and ecological farming are all proposed as alternatives. These alternatives also meet resistance, and sometimes include clashing worldviews. Where do the societal and agricultural challenges come from, what are the perspectives that clash, and what makes this issues so persistent?

In this course, first year students in agro-technology get acquainted in a social scientific manner with societal controversies that sustainability transitions to agriculture evoke. They will learn about past and current Dutch agricultural policies and politics in an international context by looking at power-differences and framings in these transitions. Students will engage in boundary-crossing activities and will apply these lessons by delving into the perspective of a stakeholder and practice the skills that are necessary to deliver an oral argumentation in the right context and for the right purpose.

Every week we will talk with an expert or professional and we will visit innovative food producers, and governmental actors. Throughout this course, students work on a stakeholder and framing analysis, and will hold a debate and dialogue about an agricultural challenge. The grade for this course is based on a group paper and a presentation.

Program/Minor

Learning Outcomes

Describe the relation and interaction between developments in biosystems engineering and society in the course of history; Analyze the perspectives and the interactions between stakeholders in current sustainability transitions in agriculture; Analyze and apply framings of sustainability transitions in agriculture and food; Defend a line of argumentation based on academic criteria; Present results based on structured arguments in a clear and attractive manner; Give constructive feedback on the argumentation of peers

Prerequisites

n/a

Details

Institution: WUR

Period: Period 2

Level: Introductory

EC: 6 ec

Philosophy of A.I. (UU)

This course will make students familiar with fundamental issues in the philosophy of AI, and will introduce them to several current discussions in the field. Students will practice their argumentation and presentation skills, both in class discussions and in writing.
The course is split up in three parts. The first part is a quick overview of the fundamental issues and core notions in philosophy of AI. It addresses topics such as the Turing Test, the Chinese Room Argument, machine intelligence, machine consciousness, weak and strong AI, and the Symbol System Hypothesis. In order to establish a shared background for all students, the material of this part will be assessed with an entrance test already in week 3.
In the second part of the course, there will be an in-depth discussion of several current topics in the field, for example on ethics and responsibility in AI, transhumanism, or the relation between AI and data science. On each topic, there will be a lecture, and a seminar with class discussions and student presentations. Students prepare for those discussions by posting a thesis with one or more supporting arguments about the required reading. In the third part of the course, students will write a philosophical paper, and will provide feedback on their fellow students’ draft papers.

Program/Minor

Learning Outcomes

missing

Details

Institution: UU

Period: Period 3

Level: Master

EC: 7.5 ec

Philosophy of AI (UvA)

In this course, we approach (the philosophy of) artificial intelligence (AI) from the perspective of theoretical philosophy. The course focuses on the discussion of the intelligence of artificial intelligence, in particular against the backdrop of the debate between nativists and empiricists. We will do so, following Cameron Buckner’s very recent book From Deep Learning to Rational Machines (OUP, 2024). We first discuss Buckner’s general framework, the debate between nativists and empiricists, and a general introduction to deep learning. In the second part of the course, we will follow Buckner’s set up discussing one cognitive capacity and one relevant classical philosopher per week.

As we focus on the issues from the perspective of theoretical philosophy, we use tools from analytic philosophy and logic to address these questions.

This course is part of the following thematic cluster(s): Language, Logic, Mind and Metaphysics; Science, Humanities, Technology and Society
The specialist topics/approaches in the course have relevance/impact for indicated fields: Mind and Cognition, Philosophy of AI, Philosophy of Technology

Program/Minor

Learning Outcomes

give an overview of the main positions within contemporary philosophy of artificial intelligence, in particular from the perspective of theoretical philosophy; explain the relationship between the philosophical study of artificial intelligence and the relevant empirical and formal research; critically analyse and present philosophical arguments in discussions; read and write philosophical texts from the field of (theoretical) philosophy of AI.

Prerequisites

An introductory level of knowledge of first-order logic and an interest in the philosophical issues surrounding artificial intelligence is expected.

Details

Institution: UvA

Period: Period 1

Level: Master

EC: 6 ec

Plant Biotechnology

During the course, lectures will be given to introduce various aspects of Plant Biotechnology. The first set of lectures outlines the techniques used in Plant Biotechnology, including recent developments such as gene editing, and in the second set, specific examples of application of these techniques and the effects on science and society are provided. Societal and ethical aspects of Plant Biotechnology are recurrent themes in the lectures, but also part of a dedicated, mandatory, work shop. During the course a plant biotech company will be visited, which will show how Plant Biotechnology is used commercially. Various laboratory techniques will be taught during hands-on practicals, covering all the steps from identification of a target gene to analysis of plants transformed to express the target gene. The practical will be supported by LabBuddy, providing an interactive learning environment. Throughout the course period, students will work on a group assignment focusing on a particular plant biotechnology case, which requires searching for and understanding of recent scientific literature. The results of this case study will be presented in an assignment report and an assignment presentation, at the end of the course.

Program/Minor

Learning Outcomes

Understand the principles behind the isolation of genes and transfer to plants, based on general understanding of gene structure and expression; Describe the analysis of gene expression and ways to regulate this; Understand the complexity of several important plant traits and the consequences of genetic modification to modify plant traits; Use genomic databases available through internet to collect and analyse plant gene sequences using bioinformatics tools; Gather and interpret relevant scientific literature on plant biotechnology topics; Apply molecular genetic and molecular biology techniques for DNA isolation, plant transformation and analysis of gene expression patterns in transgenic plants; Evaluate and discuss the (im)possibilities of plant biotechnology applications from a technical and a societal point of view

Prerequisites

Assumed: Cell Biology; Fundamentals of Genetics; practical lab skills (e.g. DNA isolation, gene cloning, PCR, as taught in PHP10306, PBR23306 or BIC10306) and general Plant biology. Mandatory: Laboratory Safety

Details

Institution: WUR

Period: Period 2

Level: Intermediate

EC: 6 ec