Results 61 to 70 of about 84,208 (297)

Random Walk Graph Auto-Encoders With Ensemble Networks in Graph Embedding

IEEE Access, 2023
Recently graph auto-encoders have received increasingly widespread attention as one of the important models in the field of deep learning. Existing graph auto-encoder models only use graph convolutional neural networks (GCNs) as encoders to learn the ...
Chengxin Xie, Xiumei Wen, Fanxing Meng, Hui Pang   +3 more
doaj   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

Molecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric, Line Bjørge, Martine Rott Lode, Cecilie Fredvik Torkildsen, Pia Aehnlich, Rammah Elnour, Daniela Elena Costea, Lars Andreas Akslen, Liv Cecilie Vestrheim Thomsen, Emmet McCormack, Katrin Kleinmanns   +10 more
wiley   +1 more source

Attention-driven Graph Clustering Network

Proceedings of the 29th ACM International Conference on Multimedia, 2021
The combination of the traditional convolutional network (i.e., an auto-encoder) and the graph convolutional network has attracted much attention in clustering, in which the auto-encoder extracts the node attribute feature and the graph convolutional network captures the topological graph feature.
Zhihao Peng 0002, Hui Liu 0032, Yuheng Jia, Junhui Hou   +3 more
openaire   +2 more sources

Enhancing Graph Summarization Using Node Importance and Graph Attention Networks

Mathematics
As the scale of graph-structured data continues to grow, graph summarization has become an important technique for storage efficiency and high-level visualization.
Krista Rizman Žalik, Domen Mongus, Mitja Žalik   +2 more
doaj   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

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, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

Molecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh, Nitzan Medina‐Itzhaki, Milena Chekov, Eden Gal‐Swisa, Roba Gabesh‐Wahabi, Inbar Savyon, Inna Naroditsky, Hilary A. Kenny, Basem Fares, Lina Korsensky, Einav Girsh, Liron Berger, Ruth Perets   +12 more
wiley   +1 more source

Adaptive Propagation Graph Convolutional Networks Based on Attention Mechanism

Information, 2022
The main steps in a graph neural network are message propagation and aggregation between nodes. Message propagation allows messages from distant nodes in the graph to be transmitted to the central node, while feature aggregation allows the central node ...
Chenfang Zhang, Yong Gan, Ruisen Yang
doaj   +1 more source

Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting

, 2023
Recent studies have shifted their focus towards formulating traffic forecasting as a spatio-temporal graph modeling problem. Typically, they constructed a static spatial graph at each time step and then connected each node with itself between adjacent ...
Philip S. Yu, Jin, H, Chuanpan Zheng, Fan, X, Wang, C, Pan, S, Peng, Z, Cheng Wang, Shirui Pan, Zonghan Wu, Haibing Jin, Zheng, C, Wu, Z, Yu, PS, Xiaoliang Fan, Zhaopeng Peng   +15 more
core   +1 more source

E2A selectively regulates TGF‐β–induced apoptosis in KRAS‐mutant non‐small cell lung cancer

Molecular Oncology, EarlyView.
Ability to induce apoptosis by TGF‐β is frequently lost in advanced lung adenocarcinoma despite intact TGF‐β signaling. We identify E2A as a mutant KRAS–dependent mediator of resistance to TGF‐β–induced apoptosis. TGF‐β induces E2A via SMAD3 in mutant KRAS cells, and E2A silencing restores apoptosis and enhances radiation response in cell lines ...
Sergei Chuikov, Shiva Krishna Katkam, Zhefan Wang, Venkateshwar G. Keshamouni   +3 more
wiley   +1 more source

A Review on Graph Theory in Deep Learning

NTU Journal of Pure Sciences
Graph theory has gained popularity as a flexible tool in machine learning to capture complex correlations between objects in non-Euclidean structured data.
Ayhan Ahmed Al-Shumam, Arjuwan M. A. Al-Jawadi   +1 more
doaj   +1 more source