About the project
The project is specific with its multidisciplinary approach in the search for potential diagnostic, prognostic or therapeutic markers. It is the combination of genetic, proteomic, histological, immunohistochemical, glycomic and analytical methods of artificial intelligence that offer the potential for more effective analysis of the findings.
The originality of the submitted activity lies in the cross-sectoral approach to biomedical research using modern machine learning and deep learning techniques based on artificial neural networks in the processing of high-dimensional, multimodal data (genetics, proteometry, histology, glycomics) in evaluation of the results, with the practical aim of creating an information model to help diagnose the project-defined cancers.
Part of the project investigation design is the analysis of the prevalence of the HPV population, enabling a better understanding of the current situation in the Slovak population, which may be important for vaccination processes today. The analysis of nitric oxide in relation to tumor transformation is also innovative. Nitric oxide may be involved in activating tumor transformation and disease progression, but may also act as an anticancer agent. The results of the project will significantly contribute to the discovery of the mechanisms of this ambivalent effect of nitric oxide in cancer. We hypothesize that the discovery of new mechanisms of nitric oxide signaling may also deliver a relevant clinical outcome.
More information about the proteomic laboratory and photos of the devices can be found in the following section
About us/laboratories/proteomic laboratory.