My Work as a Ph.D. student

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

Selected Publications, Presentations, and Posters

Data splitting to avoid information leakage with DataSAIL (2025)
Joeres, R., Blumenthal, D. B., and Kalinina, O. V.
Article in Nature Communications (Preprint in bioRxiv)
Contributed talk at Helmholtz AI Conference 2025 in Karlsruhe, Germany

Higher-Order Message Passing for Glycan Representation Learning (2024)
Joeres, R., Bojar, D.
Article in arXiv
Poster at the MLSB Workshop @ NeurIPS 2024 in Vancouver, Canada

Guiding questions to avoid data leakage in biological machine learning applications (2024)
Bernett, J., Blumenthal, D. B., Grimm, D. G., Haselbeck, F., Joeres, R., Kalinina, O. V., List, M.
Article in Nature Methods

GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES (2023)
Joeres, R., Bojar, D., and Kalinina, O. V.
Article in Journal of Cheminformatics (Preprint in bioRxiv)
Poster at 17th German Conference on Cheminformatics 2022 in Garmisch-Partenkirchen, Germany

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

Click here for the complete list of contributions.

Summerterm 2023

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

Summer School: School for Molecular and Theoretical Biology
Faculty at KalininaLab in Yerevan, Armenia

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

Summer School: School for Molecular and Theoretical Biology
Faculty at KalininaLab (remotely)

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
Addressing data leakage in a deep learning model for predicting small molecule substrates of enzymes

Bachelor Thesis

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