The Bioinformatics research group of the Center for Statistics aims to develop novel methodologies and software tools for the processing, analysis and integration of high-throughput omics data, including mass spectrometry-based proteomics. We advance research in various topics like, e.g., automated protein identification algorithms, data integration workflows with strong focus on quality control, advanced methods for protein quantification, low-level spectral modeling, statistical tools for mass spectrometry imaging analysis, and techniques to analyze, predict and model protein structures. The long term objective of the proteomics research line is to contribute to cheaper and better biomarkers for personalized medicine.
We provide research, training and consultancy services in bioinformatics and offer a Bioinformatics specialization tract in our master of statistics educational program.
Next to (statistical) bioinformatics, CenStat unites teaching, research and consultancy in biostatistics, mathematical statistics and epidemiology and public health.
For more information about the proteomics work, contact email@example.com.