Variational graph autoencoder for reconstructed transcriptomic data associated with NLRP3 mediated pyroptosis in periodontitis
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-86455-4
Abstract: The NLRP3 inflammasome, regulated by TLR4, plays a pivotal role in periodontitis by mediating inflammatory cytokine release and bone loss induced by Porphyromonas gingivalis. Periodontal disease creates a hypoxic environment, favoring anaerobic bacteria survival and… read more here.
Keywords: periodontitis; pyroptosis; nlrp3 mediated; variational graph ... See more keywords
VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell–cell communication network
Sign Up to like & getrecommendations! Published in 2024 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbae619
Abstract: Abstract Cell–cell communication plays a critical role in maintaining normal biological functions, regulating development and differentiation, and controlling immune responses. The rapid development of single-cell RNA sequencing and spatial transcriptomics sequencing (ST-seq) technologies provides essential… read more here.
Keywords: cell cell; vgae cci; cell; variational graph ... See more keywords
Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks.
Sign Up to like & getrecommendations! Published in 2023 at "Nucleic acids research"
DOI: 10.1093/nar/gkad450
Abstract: In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples… read more here.
Keywords: cell; variational graph; gene knockout; single cell ... See more keywords
Locational False Data Injection Attack Detection in Smart Grid Using Recursive Variational Graph Autoencoder
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3526672
Abstract: Stealthy false data injection attack (FDIA) that intentionally modifies measurement data of smart grid meters to bypass the traditional bad data detection module is one of menacing cyber attacks in smart grid. Due to requiring… read more here.
Keywords: detection; smart grid; graph autoencoder; false data ... See more keywords
Efficient Spiking Variational Graph Autoencoders for Unsupervised Graph Representation Learning Tasks
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Intelligent Systems"
DOI: 10.1109/mis.2024.3391937
Abstract: Variational graph autoencoders (VGAEs) are popular artificial neural network (ANN)-based models for unsupervised graph representation learning tasks, including link prediction and graph generation, which are critical in many real-world applications. Despite the promising results of… read more here.
Keywords: learning tasks; graph autoencoders; graph representation; variational graph ... See more keywords
DVGMAE: Self-Supervised Dynamic Variational Graph Masked Autoencoder
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2025.3583045
Abstract: Although contrastive self-supervised learning (SSL) on dynamic graphs has made significant success, the issue of heavy reliance on data augmentation and training tricks has been a persistent pain point. Generative SSL, especially masked autoencoders (MAEs)… read more here.
Keywords: self supervised; graph masked; graphs; dynamic graphs ... See more keywords
Variational Graph Neural Network Based on Normalizing Flows
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Signal and Information Processing over Networks"
DOI: 10.1109/tsipn.2025.3530350
Abstract: Graph Neural Networks (GNNs) have recently achieved significant success in processing non-Euclidean datasets, such as social and protein-protein interaction networks. However, these datasets often contain inherent uncertainties, such as missing edges between nodes that are… read more here.
Keywords: distribution; normalizing flows; graph neural; neural network ... See more keywords