My Work as a Ph.D. student

My work focuses on explainable and generalizable methods to predict drug-target interactions

Publications, Presentations, and Posters

2024

Higher-Order Message Passing for Glycan Representation Learning
Authors: Joeres, R., Bojar, D.
Article in arXiv

Guiding questions to avoid data leakage in biological machine learning applications
Authors: Bernett, J., Blumenthal, D. B., Grimm, D. G., Haselbeck, F., Joeres, R., Kalinina, O. V., List, M.
Article in Nature Methods

Navigating the Maze of Mass Spectra: A Machine-Learning Guide to Identifying Diagnostic Ions in O-Glycan Analysis
Authors: Urban, J., Joeres, R., Thomès, L., Thomsson, K. A., Bojar, D.
Article in Analytical and Bioanalytical Chemistry (and bioRxiv)

2022

Chair for Drug Bioinformatics
Poster at 1st General PhD Assembly 2022 at HZI in Braunschweig, Germany,

2021

Multiple Sequence Alignment using Deep Reinforcement Learning
Author: Joeres, R.
Article in Proccedings of the Studierendenkonferenz Informatik (SKILL) 2021 online and in Berlin, Germany

Teaching

Summerterm 2024

Lecture: Bioinformatik 2
Website, Teaching Assistant, joint lecture of Chair for Drug Bioinformatics and Chair for Data Driven Drug Design

(Pro-)Seminar: Comparison and Clustering of Biological Molecules
Website, Teaching Assistant at Chair for Drug Bioinformatics

Summerterm 2023

Seminar: Explainable Artificial Intelligence
Website, Teaching Assistant at Chair for Drug Bioinformatics

Summerterm 2022

Seminar: Deep Learning for Drug Discovery
Website, Teaching Assistant, joint seminar of Chair for Drug Bioinformatics and Chair for Modeling and Simulation

Project-Seminar: Data Science and Artificial Intelligence
Website, Tutor, joint seminar of many chairs at Saarland University, lead: Big Data Analytics Group

Summerterm 2021

Lecture: Statistics Lab
Website, Tutor at Chair of Computer Science and Computational Linguistics

Summerterm 2020

Lecture: Statistics Lab
Website, Tutor at Chair of Modeling and Simulation

Thesis Supervision

Master Thesis

Predicting Protein Binding Residues in an Interpretable Way (co-supervised)
Bioinformatics and Machine Learning Methods for Predicting Protein-RNA Interactions

Bachelor Thesis

Antigen Conditioned Antibody Generation and Optimization using Deep Learning Methods
Using Weisfeiler-Lehman kernels to compare protein graphs (co-supervised)