AIMC Topic: Graph Neural Networks

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A new strategy for Cas protein recognition based on graph neural networks and SMILES encoding.

Scientific reports Apr 30, 2025
The CRISPR-Cas system, an adaptive immune mechanism found in bacteria and archaea, has evolved into a promising genomic editing tool, with various types of Cas proteins playing a crucial role. In this study, we developed a set of strategies for minin...
Databases, Protein CRISPR-Cas Systems Graph Neural Networks CRISPR-Associated Proteins Neural Networks, Computer Computational Biology
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Leveraging advanced graph neural networks for the enhanced classification of post anesthesia states to aid surgical procedures.

PloS one Apr 25, 2025
Anesthesia plays a pivotal role in modern surgery by facilitating controlled states of unconsciousness. Precise control is crucial for safe and pain-free surgeries. Monitoring anesthesia depth accurately is essential to guide anesthesiologists, optim...
Machine Learning Wakefulness Graph Neural Networks Algorithms Humans Anesthesia Brain Neural Networks, Computer
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Neuro-Modulation Analysis Based on Muscle Synergy Graph Neural Network in Human Locomotion.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 16, 2025
The coordination of muscles in human locomotion is commonly understood as the integration of motor modules known as muscle synergies. Recent research has delved into the adaptation of muscle synergies during the acquisition of new motor skills. Howev...
Young Adult Adult Biomechanical Phenomena Humans Locomotion Muscle, Skeletal Neural Networks, Computer Male Algorithms Graph Neural Networks Electromyography Female Lower Extremity Walking
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Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks.

Medical image analysis Apr 9, 2025
Multimodal neuroimaging data modeling has become a widely used approach but confronts considerable challenges due to their heterogeneity, which encompasses variability in data types, scales, and formats across modalities. This variability necessitate...
Humans Neural Networks, Computer Connectome Diffusion Tensor Imaging Magnetic Resonance Imaging Graph Neural Networks Brain Multimodal Imaging
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Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma.

BMC cancer Apr 9, 2025
OBJECTIVE: The assessment of immunotherapy plays a pivotal role in the clinical management of skin melanoma. Graph neural networks (GNNs), alongside other deep learning algorithms and bioinformatics approaches, have demonstrated substantial promise i...
Melanoma Skin Neoplasms Tumor Microenvironment Neural Networks, Computer Prognosis Computational Biology Immunotherapy Gene Expression Regulation, Neoplastic Gene Expression Profiling Transcriptome Biomarkers, Tumor Humans Graph Neural Networks
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HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions.

Journal of chemical information and modeling Apr 4, 2025
Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water's remarkable versatility as a solvent. However, accurately predicting...
Graph Neural Networks Hydrolysis Neural Networks, Computer Hydrogen-Ion Concentration Thermodynamics
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Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.

IEEE journal of biomedical and health informatics Apr 4, 2025
Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diagnosis using fundus images can effectively prevent further diseases and provide targeted treatment plans for patients. Recent deep learning models for ...
Graph Neural Networks Image Interpretation, Computer-Assisted Retinal Diseases Deep Learning Humans Neural Networks, Computer Fundus Oculi
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Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks.

Journal of chemical information and modeling Mar 31, 2025
Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis, reducing the cost of drug development. Unlike traditional one-dimensional (1D) sequence-based methods, GNNs leverage graph structures to capture ric...
Pharmaceutical Preparations Graph Neural Networks Neural Networks, Computer Drug Discovery Proteins
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DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Journal of chemical information and modeling Mar 27, 2025
Machine learning potentials (MLPs) have revolutionized molecular simulation by providing efficient and accurate models for predicting atomic interactions. MLPs continue to advance and have had profound impact in applications that include drug discove...
Software Molecular Dynamics Simulation Neural Networks, Computer Quantum Theory Graph Neural Networks
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GraphDeep-hERG: Graph Neural Network PharmacoAnalytics for Assessing hERG-Related Cardiotoxicity.

Pharmaceutical research Mar 26, 2025
PURPOSE: The human Ether-a-go-go Related-Gene (hERG) encodes rectifying potassium channels that play a significant role during action potential repolarization of cardiomyocytes. Blockade of the hERG channel by off-target drugs can lead to long QT syn...
Graph Neural Networks Potassium Channel Blockers Computer Simulation Deep Learning ERG1 Potassium Channel Humans Cardiotoxicity Algorithms Neural Networks, Computer Ether-A-Go-Go Potassium Channels Machine Learning Action Potentials
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