BSc and MSc Thesis Subjects of the Bioinformatics Group
On this page you can find an overview of the BSc and MSc thesis topics that are offered by our group. The procedure to find the right thesis project for you is described below.
MSc thesis: In the Bioinformatics group, we offer a wide range of MSc thesis projects, from applied bioinformatics to computational method development. Here is a list of available MSc thesis projects. Besides the fact that these topics can be pursued for a MSc thesis, they can also be pursued as part of a Research Practice.
BSc thesis: As a BSc student you will work as an apprentice alongside one of the PhD students or postdocs in the group. You will work on your own research project, closely guided by your supervisor. You will be expected to work with several tools and/or databases, be creative and potentially overcome technical challenges. Below you will find short descriptions of the research projects of our PhDs and Postdocs. In addition you can take a look at the list of MSc thesis projects above.
Procedure for WUR students:
- Request an intake meeting with one of our thesis coordinators by filling out the MSc intake form or BSc intake form and sending it to thesis@bioinformatics.nl
- Contact project supervisors to discuss specific projects that fit your background and interest
- Upon a match, take care of the required thesis administration together with your supervisor(s) and enroll in the thesis BrightSpace site to find more information on a thesis in the Bioinformatics group
Procedure for non-WUR students or students in other non-standard situations: We have limited space for interns from other institutes. If you are interested, please email our thesis coordinators at thesis@bioinformatics.nl; please attach your CV and indicate what are your main research interests.
BSc thesis topics
Linking the metabolome and genome
The central theme of my research is the integration of metabolome and genome mining tools to accelerate and improve functional annotations of biosynthesis genes and specialized molecules. One the one hand, I am working on improving workflows to maximize the structural information obtained from mass spectrometry fragmentation data. On the other hand, I will develop and extend existing workflows that recognize patterns of co-localized genes in predicted biosynthesis genes clusters. Both the metabolomics and genomics workflows focus on the recognition of molecular substructures as building blocks of more complex natural products. As these tools will provide complementary structural data on the specialized molecules produced by microbes, fungi, and plants, I will finally integrate those workflows to boost natural product discovery.
Linking metagenomics and metatranscriptomics to study the endophytic root microbiome
Like most higher organisms, plants have a microbiome that protects them against diseases and stimulates their growth. In this project, we will study the microbial community that lives inside plant roots. By linking metagenomics and metatranscriptomics, we attempt to find out what the function of these microbes is and how they interact with each other, with pathogens and with the plant. Microbes and plants produce a wide array of secondary metabolites, which are used to interact with other organisms in their environment. Secondary metabolites can function as antibiotics, pigments, and effectors. Additionally, they can help with nutrient acquisition and communication. The genes encoding the pathways for secondary metabolites are often co-localised in clusters on the genome. Over 700 of these so-called biosynthetic gene clusters (BGCs) have been predicted to be present in the endophytic root microbiome. We want to know which BGCs are involved in pathogen suppression and what their exact function is.
Exploiting variation in lettuce and its wild relatives
Advancing in the genome era, sequencing one’s plants for the identification of variation underlying traits of interest is more accessible than ever. Comparing results between species has therefore become important as well (comparative genomics). In this research, which is part of the LettuceKnow project (https://lettuceknow.nl/ ), we use a pangenomic approach to search for genomic and transcriptomic variation across species within the genus Lactuca that can explain traits lettuce breeders are interested in. A pangenome is a hypothetical construct in which multiple fully sequenced genomes are combined into one representative reference genome. Specifically, we aim to develop new functionalities within the pangenomic framework PanTools (which is being developed at Wageningen University) to integrate genomic, transcriptomic and phenotypic data for accurate interspecies comparisons. These functionalities are immediately used for the analysis of the large amounts of sequencing and phenotype data within LettuceKnow, which will be a starting point for collaboration with molecular biologists.