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Graph Neural Networks

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ZeRPI: A graph neural network model for zero-shot prediction of RNA-protein interactions.

Methods (San Diego, Calif.) 39892680
RNA-protein interactions are crucial for biological functions across multiple levels. RNA binding proteins (RBPs) intricately engage in diverse biological processes through specific RNA molecule interactions. Previous studies have revealed the indisp...
Algorithms Computational Biology Graph Neural Networks Humans Machine Learning Neural Networks, Computer Protein Binding RNA RNA-Binding Proteins
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Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks.

Journal of chemical information and modeling 39862160
Accurately predicting activation energies is crucial for understanding chemical reactions and modeling complex reaction systems. However, the high computational cost of quantum chemistry methods often limits the feasibility of large-scale studies, le...
Graph Neural Networks Machine Learning Neural Networks, Computer Quantum Theory Thermodynamics
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IL-6-Inducing Peptide Prediction Based on 3D Structure and Graph Neural Network.

Biomolecules 39858493
Interleukin-6 (IL-6) is a potent glycoprotein that plays a crucial role in regulating innate and adaptive immunity, as well as metabolism. The expression and release of IL-6 are closely correlated with the severity of various diseases. IL-6-inducing ...
Amino Acid Sequence Graph Neural Networks Humans Interleukin-6 Neural Networks, Computer Peptides
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MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning.

International journal of biological macromolecules 39848362
Protein-protein interactions (PPI) are crucial for understanding numerous biological processes and pathogenic mechanisms. Identifying interaction sites is essential for biomedical research and targeted drug development. Compared to experimental metho...
Algorithms Binding Sites Computational Biology Graph Neural Networks Models, Molecular Neural Networks, Computer Protein Binding Protein Conformation Protein Interaction Mapping Proteins
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A Novel session-based recommendation system using capsule graph neural network.

Neural networks : the official journal of the International Neural Network Society 39842340
Session-based recommendation systems (SBRS) are essential for enhancing the customer experience, improving sales and loyalty, and providing the possibility to discover products in dynamic and real-world scenarios without needing user history. Despite...
Algorithms Graph Neural Networks Humans Neural Networks, Computer
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SIRE: Scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks.

Medical image analysis 39842325
The orientation of a blood vessel as visualized in 3D medical images is an important descriptor of its geometry that can be used for centerline extraction and subsequent segmentation, labeling, and visualization. Blood vessels appear at multiple scal...
Algorithms Graph Neural Networks Humans Imaging, Three-Dimensional Neural Networks, Computer
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A graph neural network approach for hierarchical mapping of breast cancer protein communities.

BMC bioinformatics 39838298
BACKGROUND: Comprehensively mapping the hierarchical structure of breast cancer protein communities and identifying potential biomarkers from them is a promising way for breast cancer research. Existing approaches are subjective and fail to take info...
Algorithms Biomarkers, Tumor Breast Neoplasms Female Graph Neural Networks Humans Mutation Neoplasm Proteins Neural Networks, Computer Protein Interaction Maps Proteomics
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Optimizing papermaking wastewater treatment by predicting effluent quality with node-level capsule graph neural networks.

Environmental monitoring and assessment 39825037
Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time access to precise and trustworthy effluent indices is crucial. Because wastewater treatment processes are complicated, nonlinear, and time-varying, it is e...
Biological Oxygen Demand Analysis Environmental Monitoring Graph Neural Networks Industrial Waste Neural Networks, Computer Waste Disposal, Fluid Wastewater Water Pollutants, Chemical Water Quality
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A universal strategy for smoothing deceleration in deep graph neural networks.

Neural networks : the official journal of the International Neural Network Society 39817981
Graph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the over-smoothing problem restricts their effectiveness in deep layers. Two key weaknesses of existing research on deep GNN models are: (1) ignoring the ben...
Algorithms Graph Neural Networks Humans Neural Networks, Computer
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A comprehensive graph neural network method for predicting triplet motifs in disease-drug-gene interactions.

Bioinformatics (Oxford, England) 39832275
MOTIVATION: The drug-disease, gene-disease, and drug-gene relationships, as high-frequency edge types, describe complex biological processes within the biomedical knowledge graph. The structural patterns formed by these three edges are the graph moti...
Algorithms Computational Biology Disease Graph Neural Networks Humans Neural Networks, Computer
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