The Institute of Bioinformatics of the Johannes Kepler University Linz lead by Prof. Hochreiter conducts internationally renowned research and provides profound education in bioinformatics. It has strong expertise in developing machine learning methods and extensive experience in data analysis of biological and medical data.

The group has developed several feature selection and classification methods for high-dimensional noisy measurements, (e.g. gene expression microarray data) and structural data (e.g. protein-scaffold interactions) which are both relevant in this project. In addition, feature selection methods for special tasks have been developed in Hochreiter's group, i.e. to identify genes belonging to certain pathways. The institute has gained an international reputation for excellence in the field of bioinformatics, e.g. for their path-breaking gene selection protocol, their P-SVM, which had been the winner at an international challenge on feature selection, or their FARMS algorithm, which is the leading method for microarray data preprocessing (normalization and summarization) and has been winner at the international Affycomp challenge.

Their research work was honored with numerous scientific awards, inter alia from the Functional Genomics Data Society (FGED) and the International Society for Computational Biology (ISCB). Currently their methods are used in various international collaborations, e.g. for identifying disease-related copy number variations in complex diseases like multiple sclerosis or Alzheimer's disease (project partner: Merck-Serono, Geneva), for copy number estimation in exon-targeted sequencing of cancer cell lines (project partner: Boehringer-Ingelheim, Vienna) and in mouse xenograft models (project partner: Dana-Farber Cancer Institute, Harvard Medical School, USA).