4 papers
Contrastive Geometric Learning Unlocks Unified Structure- and Ligand-Based Drug Design
Lisa Schneckenreiter, Sohvi Luukkonen, Lukas Friedrich +2
Structure-based and ligand-based computational drug design have traditionally relied on disjoint data sources and modeling assumptions, limiting their joint use at scale. In this w…
MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs
Christoph Bartmann, Johannes Schimunek, Mykyta Ielanskyi +3
A molecule's properties are fundamentally determined by its composition and structure encoded in its molecular graph. Thus, reasoning about molecular properties requires the abilit…
Measuring AI Progress in Drug Discovery: A Reproducible Leaderboard for the Tox21 Challenge
Antonia Ebner, Christoph Bartmann, Sonja Topf +3
Deep learning's rise since the early 2010s has transformed fields like computer vision and natural language processing and strongly influenced biomedical research. For drug discove…
Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl +7
Language models for biological and chemical sequences enable crucial applications such as drug discovery, protein engineering, and precision medicine. Currently, these language mod…