Treatment of inflammatory skin diseases is challenging. We are interested in unraveling molecular mechanisms of rare (genetic) dermatoses and rare lymphoproliferative disorders of the skin. In particular our research is focused on the signaling pathways that are affected in acantholytic disorders of the skin, specifically in immune cells. Another focus is the investigation of the mechanisms of extracorporeal photopheresis (ECP), a type of phototherapy that has had high success rates for more than thirty years. We are especially interested in how ECP works in patients with cutaneous T-cell lymphoma.

PI: Wolfram Hoetzenecker

Our machine learning projects are performed in close collaboration with the Institute for Machine Learning (JKU Linz). We analyze imagedata using neuronal networks. Primarily, we use histopathologic images to train a computer to detect different cancer entities in these histological images. Major challenges in this field are the lack of available data, huge size of histopathological images and the difficult interpretability of deep neural networks. We aim to overcome these challenges by creating and publishing a histopathological whole slide image data base, developing machine learning algorithms that effectively deal with gigapixel data and applying and developing different methods for interpretability.

PI: Wolfram Hötzenecker

IgE and non-IgE mediated mastcell and basophil activation play a key role in allergies and other mastcell-mediated diseases. Regulatory mechanism that could influence these cell activations are not well understood. The research group focuses on investigating mechanism that could dampen or enhance effector cell activation, with a specific focus on IgE-IgE receptor interaction.

PI: Sabine Altrichter