Results 61 to 70 of about 110,849 (310)
Dual-channel deep graph convolutional neural networks
Frontiers in Artificial IntelligenceThe dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance of various subsequent machine learning tasks.
Zhonglin Ye +15 more
doaj +1 more source
Graph Neural Network: A Comprehensive Review on Non-Euclidean Space
IEEE Access, 2021 This review provides a comprehensive overview of the state-of-the-art methods of graph-based networks from a deep learning perspective. Graph networks provide a generalized form to exploit non-euclidean space data.
Nurul A. Asif +11 more
doaj +1 more source
Graph Neural Networks Designed for Different Graph Types: A Survey
, 2023 Graphs are ubiquitous in nature and can therefore serve as models for many practical but also theoretical problems. For this purpose, they can be defined as many different types which suitably reflect the individual contexts of the represented problem ...
Holzhüter, Clara Juliane +3 more
core +1 more source
FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
Graph neural network driven traffic prediction technology:review and challenge
物联网学报, 2021 With the rapid development of Internet of things and artificial intelligence technology, accurate analysis and prediction of traffic data have become the primary target of intelligent transportations.In recent years, the method of traffic forecasting has
Yi ZHOU +5 more
doaj +2 more sources
Molecular Oncology, EarlyView.Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau +36 more
wiley +1 more source
Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma
Molecular Oncology, EarlyView.The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic +5 more
wiley +1 more source
Degree-Aware Graph Neural Network Quantization
Entropy, 2023 In this paper, we investigate the problem of graph neural network quantization. Despite the great success on convolutional neural networks, directly applying current network quantization approaches to graph neural networks faces two challenges.
Ziqin Fan, Xi Jin
doaj +1 more source
Learning Graph Neural Networks with Positive and Unlabeled Nodes
, 2021 Graph neural networks (GNNs) are important tools for transductive learning tasks, such as node classification in graphs, due to their expressive power in capturing complex interdependency between nodes.
Du, L +7 more
core +1 more source
Molecular Oncology, EarlyView.Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova +14 more
wiley +1 more source