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Found 3 papers, 1 papers with code
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks
Directed evolution as a widely-used engineering strategy faces obstacles in finding desired mutants from the massive size of candidate modifications.
Graph Representation Learning for Interactive Biomolecule Systems
Advances in deep learning models have revolutionized the study of biomolecule systems and their mechanisms.
How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images
Existing solutions heavily rely on convolutional neural networks (CNNs) for global pixel-level analysis, leaving the underlying local geometric structure such as the interaction between cells in the tumor microenvironment unexplored.
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