8 citations · 15 across the 6 of their papers we have counts for
7 papers
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…
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…
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…
Predicting hydration free energies of the FreeSolv database of druglike molecules with molecular density functional theory
Sohvi Luukkonen, Luc Belloni, Daniel Borgis +1
We assess the performance of molecular densityfunctional theory (MDFT) to predict hydration freeenergies of the small drug-like molecules benchmark,FreeSolv. MDFT in the hyper-nett…
Pressure Correction for Solvation Theories
Anton Robert, Sohvi Luukkonen, Maximilien Levesque
Liquid state theories such as integral equations and classical density functional theory often overestimate the bulk pressure of fluids because they require closure relations or tr…