Current & Previous Projects
In this ongoing project we are combining and extracting information from several data bases with the goal to facilitate compatibility of RNA expression data acquired though different methods. We aim to build coefficents to compare in situ data to qPCR data.
Stay tuned for more information on this project!
This project is a collaboration with Delf-Magnus Kummerfeld and Timofey S Rozhdestvensky (Medical Faculty, Core Facility Transgenic Animal and Genetic Engineering Models (TRAM)).
The performance of Graph Neural Networks (GNNs) relies on the quality of the graph structure and thus noisy and incomplete graphs lead to poor model output. Graph Structure Learning (GSL) is a procedure to improve the graph structure by removing and adding edges and/or changing edge weights of the original graph. Since high-quality biolo- gical datasets are hard to come by and the available ones are often incomplete and noisy, GSL should be used to improve the quality of the original graph. In my master thesis I want to address this problem and work on a solution using heterogeneous graph structure learning to infer associations between microRNAs, a type of non-coding RNA, and diseases using an interaction network of non-coding and protein coding genes. This approach may improve the predictive performance compared to models using only the original graph structure to infer microRNA - disease associations.
Supervised by Ngan Dong, M.Sc. and Dr. Megha Khosla, L3S Research Center Hannover.
Research has found issues that developers are facing while implementing secure applications in Android Studio, even after the Network Security Configuration was introduced and updated to more secure default configurations some flaws weren’t addressed in the latest version1. In my bachelor thesis I addressed these problems and proposed a solution in form of a plug-in for Android Studio. The features of the plug-in cover wrong root tags, allowed cleartext traffic, malformed domains and self-signed certific- ates by providing code highlighting, mouse over texts and quick fixes for the developer. Therefore this plug-in can help developers to easily detect security issues and assists in correcting them. To meet my design goals of providing help that is easy to understand and visible but not distracting, I conducted a focus group while developing the plug-in.
Supervised by Nicolas Huaman, M.Sc. and Prof. Sascha Fahl, USEC Hannover.