Klaus, Mike (MSc)
Mike Klaus
AIComB, TEcoEvo, BioMeDS
Research Background
During my time with the BioMedical Data Science group, I worked on medical image data including cardiac magnetic resonance images (MRI) and photon-counting computed tomography (PC-CT) images of the head. My main interests encompass programming and its application to biological research.
Current Research Project
My current project brings together genomic data and medical imaging data from large biobanks such as the UK Biobank. My work aims to research prospective markers for Fabry’s disease and quantify the pathogenicity of variants of the GLA gene involved in this lysosomal storage disorder. A key objective is to create a fitness landscape model that predicts fitness values for previously unknown mutations of the GLA gene and to determine whether epistasis plays a major role in Fabry’s disease.
Research Interests
- Medical imaging data analysis (MRI, CT)
- Computational and programming approaches to biology
- Genetic variant analysis
- Fabry’s disease and lysosomal storage disorders
- GLA gene mutations and pathogenicity
- 2025-ongoing Promotion (Dr. rer. nat)
Julius Maximilian University Würzburg, Würzburg, Germany
- 2023-2025 Master of Science in Biosciences
Julius Maximilian University Würzburg, Würzburg, Germany
Project: Applying machine learning based denoising to photon-counting CT images
- 2018-2023 Bachelor of Science in Biology
Julius Maximilian University Würzburg, Würzburg, Germany
Thesis: Dynamic Radiomics in cardiac MRI
