DSSC in Healthcare and Pharmacy
Modern health care makes use of a complex arrangement of diagnostic methods and tools
involving mathematical analysis and ICT. The massive amount of data collected daily can lead to personalized modelling of the health situation of any individual, to early diagnosis of diseases, and personalized advice that can help people stay healthy longer. Insights from systems and control and complexity theory can boost the development of robotic prostheses that offer better, intuitive mobility and biocompatibility.
The DSSC research contributes to systems biology; computer diagnosis; architecting complex healthcare systems; analysis and management of cognitive functions; prosthetics; precision medicine; epidemiological dynamics. The Centre contributes to Pharmacy research with work on data management systems for I/O- and CPU-intensive data processing workflows for mass spectrometry; infrastructure for integrated ‘multi-omics projects’; and integration of proteomics and metabolomics data with genetics; visualization of genomics, proteomics and metabolomics networks.Examples of relevant projects:
- Automatic identification of structures in biomedical mega-images
- Segmentation and classification of intracellular structures in microscopy (this research is developed by the DSSC member Lambert Schomaker within the European-funded PERICO project coordinated by Prof. Prof. Dr. Ida J. van der Klei)
- Computational Design of Soft Robots
- Coevolutionary Dynamic Networks
- Clinical Big Data for multifactorial diseases: from molecular profiles to precision medicine
- Uncovering the information processing underlying the interactions between brain areas
Thematic application includes:
- From brain imaging to microscopy image processing
- Heterogeneous time-series problems (spreadsheets): prediction and classification
- Optimization and control problems (systems & control, reinforcement learning)
- Software engineering: interoperability, security and anonymization
- Network analysis (metabolism, proteomics) and causality
- Sequence analysis (virus-mutation prediction, RNA, DNA)
TestimonialsModern healthcare is all about data. An abundance of data, also including measurements and imaging data, is collected by people themselves (quantified self) but also by healthcare institutions. To allow medical experts to obtain a proper diagnosis and determine the correct treatment these data have to be interpreted. Because of the wealth of data this increasingly becomes a challenge where data science will play a pivotal role in the future. Therefore, data scientists such as trained in DSSC will be increasingly employed in healthcare institutions in the future to help collect, analyze and interpret the collected data. Peter van Ooijen, Discipline leader, Center for Medical Imaging North East Netherlands, scientific researcher University Medical Centre Groningen.
The expertise in statistics, Bayesian models and data science at the DSSC helps us to reconstruct molecular networks from quantitative molecular data in cancer and chronic obstructive pulmonary disease development, which we aim to translate into novel clinical diagnostics allowing more efficient personalized treatments.
Peter Horvatovich, Groningen Institute of Pharmacy.
|Last modified:||29 April 2021 4.23 p.m.|