New AI Model Predicts Molecular Toxicity Using 3D Geometry
A new AI framework called MolMMP improves molecular toxicity prediction by integrating SMILES sequences, graph topology, and 3D geometric data.
A new AI framework called MolMMP improves molecular toxicity prediction by integrating SMILES sequences, graph topology, and 3D geometric data.
Researchers have developed GraphPepTox, a geometric deep learning framework that models spatial residue relationships to improve peptide toxicity prediction.
A new clustering algorithm called 3L-GBC models dense, transitional, and sparse regions within clusters using granular balls to better handle ...
© 2026 Scienmag - Science Magazine
© 2026 Scienmag - Science Magazine