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Graph Neural Networks

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GraphPhos: Predict Protein-Phosphorylation Sites Based on Graph Neural Networks.

International journal of molecular sciences 39940709
Phosphorylation is one of the most common protein post-translational modifications. The identification of phosphorylation sites serves as the cornerstone for protein-phosphorylation-related research. This paper proposes a protein-phosphorylation site...
Algorithms Amino Acid Sequence Computational Biology Graph Neural Networks Neural Networks, Computer Phosphorylation Protein Processing, Post-Translational Proteins Software
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UNAGI: Unified neighbor-aware graph neural network for multi-view clustering.

Neural networks : the official journal of the International Neural Network Society 39923340
Multi-view graph refining-based clustering (MGRC) methods aim to facilitate the clustering of data via Graph Neural Networks (GNNs) by learning optimal graphs that reflect the underlying topology of the data. However, current MGRC approaches are limi...
Algorithms Cluster Analysis Graph Neural Networks Humans Neural Networks, Computer
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Fine-scale striatal parcellation using diffusion MRI tractography and graph neural networks.

Medical image analysis 39954340
The striatum, a crucial part of the basal ganglia, plays a key role in various brain functions through its interactions with the cortex. The complex structural and functional diversity across subdivisions within the striatum highlights the necessity ...
Algorithms Corpus Striatum Diffusion Tensor Imaging Graph Neural Networks Humans Image Processing, Computer-Assisted Neural Networks, Computer
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Deciphering and Mitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems with Knowledge-Infused Graph Neural Network.

Environmental science & technology 39936390
Deciphering and mitigating dynamic greenhouse gas (GHG) emissions under environmental fluctuation in urban drainage systems (UDGSs) is challenging due to the absence of a high-prediction model that accurately quantifies the contributions of biologica...
Graph Neural Networks Greenhouse Gases Methane Neural Networks, Computer Nitrous Oxide Wastewater
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Generative and contrastive graph representation learning with message passing.

Neural networks : the official journal of the International Neural Network Society 39922157
Self-supervised graph representation learning (SSGRL) has emerged as a promising approach for graph embeddings because it does not rely on manual labels. SSGRL methods are generally divided into generative and contrastive approaches. Generative metho...
Autoencoder Datasets as Topic Generative Artificial Intelligence Graph Neural Networks Supervised Machine Learning
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CL-GNN: Contrastive Learning and Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling 39913849
In the realm of drug discovery and design, the accurate prediction of protein-ligand binding affinity is of paramount importance as it underpins the functional interactions within biological systems. This study introduces a novel self-supervised lear...
Drug Discovery Graph Neural Networks Ligands Machine Learning Neural Networks, Computer Protein Binding Proteins
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Scaling Graph Neural Networks to Large Proteins.

Journal of chemical theory and computation 39913331
Graph neural network (GNN) architectures have emerged as promising force field models, exhibiting high accuracy in predicting complex energies and forces based on atomic identities and Cartesian coordinates. To expand the applicability of GNNs, and m...
Graph Neural Networks Machine Learning Molecular Dynamics Simulation Neural Networks, Computer Proteins Thermodynamics
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Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.

Scientific reports 39900572
Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the...
Adult Algorithms Convolutional Neural Networks Electroencephalography Female Graph Neural Networks Humans Male Models, Neurological Nerve Net Schizophrenia
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AFMDD: Analyzing Functional Connectivity Feature of Major Depressive Disorder by Graph Neural Network-Based Model.

Journal of computational biology : a journal of computational molecular cell biology 39899351
The extraction of biomarkers from functional connectivity (FC) in the brain is of great significance for the diagnosis of mental disorders. In recent years, with the development of deep learning, several methods have been proposed to assist in the di...
Algorithms Biomarkers Brain Deep Learning Depressive Disorder, Major Graph Neural Networks Humans Neural Networks, Computer
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A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features.

BMC public health 39893390
BACKGROUND: Accurate and timely monitoring of influenza prevalence is essential for effective healthcare interventions. This study proposes a graph neural network (GNN)-based method to address the issue of cross-regional connectivity in predicting in...
Disease Outbreaks Forecasting Graph Neural Networks Humans Influenza, Human Neural Networks, Computer Spatio-Temporal Analysis
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