Artificial Intelligence; Data Interpretation, Statistical; Epidemiology; Genomics; Metagenomics
My main research focus at the Medical University of Vienna evolves around several data-science, machine learning and next generation sequencing (NGS) related topics. I am studying the skin microbiome, specifically the intricate relationship between skin bacteria and bacteriophages. In this field, I am actively involved in the development of methods to identify lytic phages suitable for phage therapy using metagenomic samples.
I have a keen interest in genetics contributing to medical genetics projects by providing genetic insights for critically ill patients at the Department of Dermatology and the Department for Laboratory Medicine. We try to set up pipelines that adhere to international standards for routine genetic testing. In this context we are also developing software to ease communication between data scienctists and medical doctors. Furthermore, I am collaborating with the Department of Epidemiology on large-scale projects, such as Genome-wide Association Studies (GWAS), utilizing the UKB-biobank dataset.
Techniques, methods & infrastructure
I was awarded a PhD in Biotechnology from the University of Life Science in Vienna in 2015. I recieved PostDoctoral training at the Department of Epidemiology and Biostatistic of the Imperial College London and worked for the 100.000 Geneomes Project before I started my current post at MedUni Wien.
In recent projects and collaborations I applied the following methods and techniques:
- Genetic analysis, WGS (https://github.com/Mwielscher/derma-genomics ) GATK pipeline running on Google cloud with increase security measures (developed in collaboration with Hatem Navar)
- scRNA sequencing (https://github.com/Mwielscher/scRNAseq ) this repository also contains instructions on how to use the Vienna Scientic cluster
- Phage discovery (https://github.com/Mwielscher/AD_phageDiscovery) scripts that help to discover phages in meta genomic samples
- Epidemiology (https://github.com/Mwielscher/EWAS_CRP ) scripts from EWAS to Mendelian Randomization
- Epidemiology II – We are running several projects analyzing data from from MedUni’s RDA (Research Documentation and Analysis platform)
- Wielscher, M. et al. (2023) ‘The phageome in normal and inflamed human skin’, Science Advances, 9(39). Available at: http://dx.doi.org/10.1126/sciadv.adg4015.
- Wielscher, M. et al. (2022) ‘DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases’, Nature Communications, 13(1). Available at: http://dx.doi.org/10.1038/s41467-022-29792-6.
- Wielscher, M. et al., 2021. Genetic correlation and causal relationships between cardio-metabolic traits and lung function impairment. Genome Medicine, 13(1). Available at: http://dx.doi.org/10.1186/s13073-021-00914-x.
- Wielscher, M. et al., 2015. Diagnostic Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD. EBioMedicine, 2(8), pp.929–936. Available at: http://dx.doi.org/10.1016/j.ebiom.2015.06.025.
- Wielscher, M. et al., 2013. Cytosine 5-Hydroxymethylation of the LZTS1 Gene Is Reduced in Breast Cancer. Translational Oncology, 6(6), pp.715–IN27. Available at: http://dx.doi.org/10.1593/tlo.13523.