/tools/Physics-aware-Multiplex-GNN
Physics-aware-Multiplex-GNN
XieResearchGroup/Physics-aware-Multiplex-GNN
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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