Lis Arend
| Position: | PhD Student |
| Email: | lis.arend(at)tum.de |
Currently, I am working as a PhD student in Bioinformatics, focusing on the development of a platform for dynamically exploring cohort-based data studies through multi-level network medicine.
In my previous role as a student research assistant, I was involved in the systematic analysis of proteomics data for the SyMBoD project and contributed to meta-analysis of proteomics bone biomarkers to identify druggable targets for improved scaffold design. My Master's thesis explored the impact of different normalization techniques on proteomics data.
Throughout my academic journey, I have been involved in the development of several tools, including an app for the FeatureCloud platform and the CYANUS platform, designed for analyzing CyTOF data and differential expression analysis.
Education & Work Experience
Doctoral Candidate in Bioinformatics at DaiSyBio,
2023 -
Technical University of Munich, Germany
Student Research Assistant at the Institute for Computational Systems Biology
2022 - 2023
University of Hamburg, Germany
Teaching Assistant at the Chair of Experimental Bioinformatics
2021
Technical University of Munich, Germany
Teaching Assistant at the Lehr- und Forschungseinheit Bioinformatik
2020-2021
Ludwig-Maximilians Universität München, Germany
MSc in Bioinformatics
2020 - 2023
Technical University of Munich and Ludwig-Maximilians Universität München, Germany
BSc in Bioinformatics
2017 - 2020
Technical University of Munich and Ludwig-Maximilians Universität München, Germany