/tools/Physics-aware-Multiplex-GNN

Physics-aware-Multiplex-GNN

XieResearchGroup/Physics-aware-Multiplex-GNN

72 stars23 forksPythonWebsiteAdded February 4, 2026
summary

PAMNet is a universal framework designed for accurate and efficient geometric deep learning of molecular systems. It excels in predicting molecular properties, such as binding affinities and RNA 3D structures, and utilizes graph neural networks to enhance performance in these tasks.

description

Source code for "A universal framework for accurate and efficient geometric deep learning of molecular systems" (Nature Scientific Reports)

topics

computational-biologycomputational-chemistrydockinggeometric-deep-learninggraph-neural-networksmachine-learningprotein-ligand-interactionsrna-structure-prediction

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