SOURCE-LINKED INTELLIGENCE

GraphNOSE: A Graph Transformer in Olfaction

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

Predicting olfactory qualities from molecular structure is an open problem in chemoinformatics. Although linear models can link molecular features to odor descriptors, they often fail when extrapolating to novel chemical scaffolds, extreme molecular weights, or complex odor mixtures. To address this, we introduce GraphNOSE, an open-source graph transformer framework that predicts multi-label odor descriptors from simplified molecular-input line-entry system (SMILES) strings for single molecules and binary mixtures. By integrating positional and structural encodings within a transformer-based g

Read original source ↗ Open in workspace

recordType

paper

region

Global