Stefanie Mühlhausen
Biography
Stefanie is a research assistant in the group of Julian Kunkel. She has a background in biology and computer science and holds a PhD in bioinformatics.
ORCID: 0000-0002-2979-8082
Research Interests
- High-Performance Computing
- Evolutionary biology
Projects
Teaching
Open Thesis Topics
Benchmarking phylogenetic tree reconstructionsApply
In phylogenetic tree reconstructions, we describe the evolutionary relationship between biological sequences in terms of their shared ancestry. To reconstruct such a tree, multiple approaches exist, including maximum likelihood and Bayesian methods. Among the most commonly used implementations of these methods are RAxML and MrBayes, both of which are available on SCC. In this project, you will identify a suitable benchmarking suite and use it to benchmark RAxML and MrBayes on SCC.
Prototyping common workflows in phylogenetic tree reconstructionsApply
In phylogenetic tree reconstructions, we describe the evolutionary relationship between biological sequences in terms of their shared ancestry. To reconstruct such a tree, multiple approaches exist, including maximum likelihood and Bayesian methods. Among the most commonly used implementations of these methods are RAxML and MrBayes, both of which are available on SCC. In this project, you will identify and establish a typical workflow on SCC, from data management to documentation. This project is especially suitable for students enrolled in Computer Science (M.Ed.) programme.
Benchmarking AlphaFold and alternative models for protein structure predictionApply
Proteins are involved in every biological process in every living cell. To assess how a protein functions exactly, knowing its amino acid sequence alone is not enough. Instead, its three-dimensional structure needs to be determined as well. In the last year, we saw a number of AI bases approaches put forward. In this project, you will compare and benchmark the performance of AlphaFold and alternative models on the SCC.
Supervised Theses
2023
- Running Kubernetes Workloads on Rootless HPC Systems using Slurm, Sören Metje (Master's Thesis), Advisors: Prof. Dr. Julian Kunkel, Stefanie Mühlhausen, 2023-12, BibTeX URL
All publications as BibTex
Publications prior joining this group listed here