COMPUTATIONAL BIOLOGY AND IMMUNO-ONCOLOGY (CBIO)
We are developing and using computational approaches for integrative analyses of multi-omics and next-generation sequencing data in order to gain a network-level view of the studied system for a variety of applications. We aim to predict and test novel drug targets, biomarkers, and biological mechanisms (e.g. immune escape) to treat cancer more effectively with a focus on cancer immunology based therapeutic solutions.
Using clinical data, immuno-genomic analyses, pharmacogenomics databases, machine learning approaches, and integrative data science strategies we aim to contribute to 1) personalized medicine and precision oncology, and 2) systems and network medicine, therapy resistance and vulnerabilities. Specific research questions are related to: – Connection of DNA damage and repair with the immunome in (ovarian) cancer – Synthetic lethal interactions determine therapeutic vulnerability of cancer – Systems analysis of microRNA-mRNA networks shaping the tumor immune environment and other disease processes – Prediction of tumor specific and viral antigens for therapeutic vaccination – Soluble and tissue based predictive and prognostic biomarker – Spatial and single cell analyses of the tumor microenvironment. |
Team
Alumni
Falk Gogolla, Markus Ausserhofer, Hendrik Gottschling, Miriam Federer, Matthias Leitner, Christoph Schatz |
Projects
– MUI/UIBK PhD program: Antimycotic resistance - approach from a one health perspective - MYCOS (Immunomodulation by intratumoral mycobiome) – OeNB Anniversary fund (PI): Connection of DNA damage and repair with the immunome in high grade serous ovarian cancer – FWF Austrian Science Fund (Co-PI): MicroRNAs as predictive biomarker for COVID-19 – Pharmaceutical & Biotech company partners: Computational cancer immunology |
Reports
Aplications of AI in IO (Book chapter) Inside precision medicine MUI news medRxiv Research square |
Publications
list of publications |