Integrating different sources of clinical and genomic data is a new resource direction for supporting diagnosis, outcome and prediction of patient survival. By drawing on the data from these platforms, the biomarker pipeline can be considerably enriched. The task is to support diagnosis and treatment outcome using new markers for specific diseases.
Of equally high interest for diagnosis and prognosis protocols is the analysis, management and mining of the tremendous volume of images and image data captured from different microscopy and analysis technologies. To do this, however, suitable modeling and statistical methods are required. The main idea is to apply different ensemble methods for each data source (specific receptors, new molecules for DNA recognition, recombinant enzymes, imaging and clinical data).
Recent research and products developed by the University include:
- diagnosis of chronic heart failure
- automatic Doppler analysis from medical images
- diagnosis of neurodegenerative disorders, in particular Huntington’s Disease (HD)
- advanced testing methods to screen genotoxic substances
- recombinant L-aspartate oxydase
- synthesis of modified PNAs to obtain new molecules for DNA recognition
- A2A adenosine receptors as biomarkers
- high-resolution FISH methodology for genomic studies
- new methods that can separate human red blood cells to study risk factors for complications in diabetes and cardiovascular diseases
- anti-oligosaccharide antibodies for breast cancer diagnosis and therapy