Research Departments Center for Molecular and Biomolecular Informatics

Center for Molecular and Biomolecular Informatics

The Center for Molecular and Biomolecular Informatics (CMBI) does research and education, and provides services in bioinformatics and cheminformatics.

Contact Head of the CMBI

Peter-Bram 't Hoen PhD
head of department

+31 (0)24 361 93 90

Mission & vision

Our mission is:

to add value to personal health data by their translation into integrative knowledge and actionable information.

Our vision 

  • CMBI develops bioinformatics approaches that contribute to the understanding of disease mechanisms, personalized therapies and interventions, and a learning health care system
  • CMBI is committed to the reusability of their data, tools, and services
  • CMBI provides  bioinformatics researchers in Radboudumc with a platform for exchange of knowledge and expertise
  • CMBI contributes to the education of BMW, MLW, and MMD students so that they can apply and understand the principles behind (existing) bioinformatics tools

Radboudumc Technology Center Bioinformatics

The Bioinformatics technology center aims to raise and solve biological questions using the most recent computer technologies and big data solutions.

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Our mission is to provide a basic understanding in Bioinformatic principles. Follow-up courses are available for those who want to gain greater insight in our field.

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Researchers at the CMBI contribute to several courses at both the Faculty of Science and the Medical Faculty. We provide courses in Structural Bioinformatics, Comparative Genomics, Data Analysis, and programming courses such as Java. We specifically focus on the Molecular Life Science students, Biomedical Sciences students and participants in the master Molecular Mechanisms of Disease, although some of our courses can be chosen by Biology, Chemistry or Medical students as well. 

Our mission is to provide a basic understanding in Bioinformatic principles for bachelor students as this was shown to be beneficial for those who want to pursue a career in Life Sciences. Follow-up courses are available for those who want to gain greater insight in our field. 

For MLS/Biology students it is even possible to follow the B-track by choosing a combination of (master) Bioinformatics courses and internships at Bioinformatics departments. 

Our researchers also teach in special interest courses and summer schools here at the Radboudumc, the Radboud University and elsewhere.


For more information, you can contact dr. Hanka Venselaar, education coordinator at the CMBI.




The CMBI offers a wide range of possibilities for internships.

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Both bachelor and master students from studies such as Molecular Life Sciences, Biomedical Sciences, Chemistry and MMD are welcome. In general, we are flexible in terms of internship length, type of internship and type of research. 

Below you can find a few examples of internships possiblities: 

title:  Analysis of microbiomes obtained with molecular inversion probe (smMIP) next gen seq and design of novel smMIPS to identify human microbiome compositions.

The metagenomes of bacterial species living in and on humans have uncovered a new angle to predicting and understanding human health and disease.
Single molecule Molecular Inversion Probes (smMIPS) allow us to derive the composition of a metagenome at unprecendented phylogenetic depth at affordable costs, facilitating large scale analyses. Design of smMIPS for large numbers of genomes, using conserved sequences for the probes, and analysis of the results requires understanding of the experimental techniques that are being used, programming skills and biological knowledge to interpret the results: typical skills of a bioinformatician. In the project the student would first analyze the data that we have already obtained about human metagenomes, using in-house developed software, and would then go on to design new smMIPS to increase the number of species and strains that we can obtain.
Programming skills: An ambition to work with large sequence datasets is required and basic programming skills (e.g. python) are strongly preferred.
Anticipated start: summer 2019
Duration: 0.5 year, or more


Title: Deconvolution of gene expression data from synovial biopsies of rheumatoid arthritis patients

Description: Analysis of gene expression in bulk tissues using RNA sequencing provides important information to understand the processes involved in disease development and progression. However, many tissues are heterogeneous and contain a mix of different cell types. This makes it difficult to identify gene expression levels specific for various cell type, since the expression level of each individual gene can differ between cell types. Disease development and progression or the response to drug therapy is often accompanied by changes in cell composition. For example, an increase of malignant cells and tumor infiltrating cells compared with surrounding cells is an indicator of tumor growth and of the clinical outcome for patients. Thus, the cellular composition of a tissue is important for the understanding of many biological processes.
Rheumatoid arthritis (RA) is a disease characterized by inflammation of multiple joints, which, if not treated, leads to irreversible joint damage. During joint inflammation cells from the immune system infiltrate in the synovial membrane, leading to the formation of so-called pannus tissue. Synovial biopsies taken from the inflamed joints of RA patients are mainly composed of synovial fibroblasts, macrophages, neutrophils, and lymphocytes. Using publicly available RNAseq datasets, as well as single-cell sequencing data, you will elucidate the constituent cell types and their proportions in synovial biopsies from RA patients by computational deconvolution of gene expression data. Deconvolution is the identification of properties and the relative abundance of components from a mixture. This project will be carried out at the Department of Biomolecular Chemistry in close collaboration with the Centre for Molecular and Biomolecular Informatics with supervision from both departments.
MSc student project
Preferred background: Bioinformatics, Computational Biology
Programming skills: work with large datasets, knowledge of R or Python is required
Anticipated start: ASAP
Length: 0.5-1 year

Title: Improving HOPE by comparing Variant Effect Predictions 

Description: HOPE is our own in-house server for the prediction of mutational effects. This server is specifically aimed at the medical scientist and produces a report that is clear and understandable for everyone without a background in structural bioinformatics. HOPE has been running for several years and is being used by researchers all over the world. In order to keep this server up to date we perform small tests in which we select mutations that were described in high-end journals such as The American Journal of Human Genetics and Nature Genetics. We compare the effect predictions made in these article with those made by our HOPE server (and eventually also with predictions made by other widely-used automatic online servers). The results should be used to improve the predictions made by HOPE.

Preferred background: MLS/BMS, evt BIO
Length: flexible, between 1-6 months.
Programming skills: not necessary

Title: Protein Protein Contact Predictions

Description: Proteins can hardly ever function on their own. Many proteins are found in homo- and heteromeric complexes, and many others are found in a transient complex at least once during their lifecycle. Interactions made by these proteins can be disturbed by mutations, which often lead a non-functional protein complex and eventually a disease. Therefore, it would be interesting to predict the effects of mutations that occur on protein surfaces. However, information about interacting residues on surfaces is still scarce and only a few protein protein interaction servers exist.
In collaboration with a research group in Amsterdam, we have linked their PPI-prediction server SERENDIP to a script that visualizes the predictions in a YASARA scene. A possible student project would be to test and analyse these predictions. 
Preferred background: MLS/BMS/BIO/MMD
Length: at least 2 months
Programming skills: basics

Title: Consensus Variant Effect Prediction

In order to correctly treat patients, it is beneficial to understand the molecular base of their disease or syndrome. Mutations that occur in the coding sequence of proteins might have effect on ligand binding, membrane anchoring, general stability/folding, interactions with other proteins, etc. Nowadays, several online servers that can analyse these effects exist. One of them is our own HOPE server, a server that can analyse the protein structure in detail and will provide an extensive report readable for the medical scientist. Other predictions servers often provide a result that contains only a binair answer (damaging or not), or a value (0 to 10). HOPE's results could be strengthened by combining its textual report with a consensus prediction that would be a combination of these other servers. 
Preferred background: master MLS/Informatics/Data science 
Length: 0.5-1 year
Programming skills: Good

Title: Timing and localization of gene expression in the DM1 locus to advance our understanding of the brain phenotype of myotonic dystrophy

Our aim is to obtain a deeper understanding of the expression of the genes in the DM1 locus (Fig. 1), the DMPK and DM1-AS transcripts in particular, during brain development, their regional expression patterns in the brain and their expression levels in different cell types present in the brain. These expression patterns can then subsequently be related to the brain abnormalities observed in DM1. In analogy to published work on DMD3, you will be using public large-scale gene expression resources from human and mice, including the Allen Brain Atlas, the FANTOM5 study and the 10x genomics mouse brain single cell dataset. You will be analyzing, comparing and interpreting the expression signatures present in these different resources.

Programming skills: An ambition to work with large datasets is required and basic programming skills (R, python) are strongly preferred.
Preferred background: MMD student project
Anticipated start: end 2018/beginning 2019


Bioinformatics Services

We maintain computational facilities, databases, and software packages in bioinformatics.

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Our researchers CMBI

A list of researchers connected to this department.

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Research groups CMBI

Discover some of our research that is related to molecular and biomolecular informatics.

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Contact Business manager

Nicolai Giling MSc
Business manager

+31 (0)24 3686538

Contact Operational manager

Barbara van Kampen
Operational manager

+31 (0)24 361 93 90

Getting there

Entrance: Radboud Institute for Molecular Life Sciences
Route: 260

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Getting there

Visiting address

Radboud Institute for Molecular Life Sciences
Geert Grooteplein 28
6525 GA Nijmegen


Enter building at: Radboud Institute for Molecular Life Sciences
Follow route 260

Research themes

Affiliated institutes

Radboud Institute for Health Sciences

This department is affiliated with RIHS. The research at this institute aims to improve clinical practice and public health. institute pages

Radboud Institute for Molecular Life Sciences

This department is affiliated with RIMLS. Their main aim is to achieve a greater understanding of the molecular mechanisms of disease. institute pages