Results 81 to 90 of about 84,208 (297)

Tumor B‐cell infiltration in platinum‐treated advanced muscle‐invasive urothelial carcinoma

Molecular Oncology, EarlyView.
Bladder tumors with higher pretreatment memory B‐cell infiltration were linked to longer survival after cisplatin chemotherapy, but not carboplatin. These tumors also showed more organized immune structures (tertiary lymphoid structures) and a shared pro‐inflammatory B‐cell‐rich community, suggesting that memory B cells may help identify patients most ...
Konrad Stawiski, Júlia Perera‐Bel, Alejo Rodriguez‐Vida, Nuria Juanpere, Jihyun Lee, Daniel E. Michaud, Jennifer L. Guerriero, Kent W. Mouw, Aristotelis Bamias, Filipe L. F. Carvalho, Joaquim Bellmunt   +10 more
wiley   +1 more source

Graph Attention Topic Modeling Network

Proceedings of The Web Conference 2020, 2020
Existing topic modeling approaches possess several issues, including the overfitting issue of Probablistic Latent Semantic Indexing (pLSI), the failure of capturing the rich topical correlations among topics in Latent Dirichlet Allocation (LDA), and high inference complexity.
Liang Yang 0002, Fan Wu, Junhua Gu, Chuan Wang 0002, Xiaochun Cao, Di Jin 0001, Yuanfang Guo   +6 more
openaire   +1 more source

Graph Attention Networks in Exchange Rate Forecasting

Econometrics
Exchange rate forecasting is an important issue in financial market analysis. Currency rates form a dynamic network of connections that can be efficiently modeled using graph neural networks (GNNs).
Joanna Landmesser-Rusek, Arkadiusz Orłowski   +1 more
doaj   +1 more source

Adaptive Structural Similarity Guided GCN–GAT Framework for Robust Link Prediction [PDF]

International Journal of Mathematical, Engineering and Management Sciences
Social Network Analysis (SNA) has experienced major advancements with the growth of technology, which has made link prediction an important aspect of SNA, particularly regarding social network applications, recommendation systems, and various biological ...
Shambhu Kumar, Dinesh C. S. Bisht, Arti Jain   +2 more
doaj   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

Supervised Attention Using Homophily in Graph Neural Networks

, 2023
Graph neural networks have become the standard approach for dealing with learning problems on graphs. Among the different variants of graph neural networks, graph attention networks (GATs) have been applied with great success to different tasks.
Vazirgiannis, Michalis, Nikolentzos, Giannis, Chatzianastasis, Michail   +2 more
core  

PAK1 activation drives divergent resistance mechanisms to aromatase inhibition and tamoxifen in a luminal: A breast cancer model

Molecular Oncology, EarlyView.
Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller, Janina Müller, Efstathios‐Iason Vlachavas, Lukas Beumers, Lena Fleischhacker, Sara Burmester, Angelika Wörner, Sabine Karolus, Dominic Helm, Cindy Körner, Stefan Wiemann   +10 more
wiley   +1 more source

Android malware detection based on graph attention networks

四川大学学报. 自然科学版, 2022
The explosive growth of Android malware has put forward more efficient and accurate requirements for malware detection methods. In the early years, detection methods were mainly based on features such as permissions and opcode sequences.
YUE Zi-Wei, FANG Yong, ZHANG Lei
doaj  

Review of Graph Neural Networks [PDF]

Jisuanji kexue
With the rapid development of artificial intelligence,deep learning has achieved great success in data that can be represented in Euclidean spaces,such as images,text,and speech.However,it has been difficult to apply deep learning to non-Eucli-dean ...
HOU Lei, LIU Jinhuan, YU Xu, DU Junwei
doaj   +1 more source

EATSA-GNN: Edge-Aware and Two-Stage attention for enhancing graph neural networks based on teacher–student mechanisms for graph node classification

Graph Neural Networks (GNNs) have fundamentally transformed the way in which we handle and examine data originating from non-Euclidean domains. Traditional approaches to imbalanced node classification problems, such as resampling, are ineffective because
Fofanah, Abdul Joseph, Leigh, Alpha Omar
core   +1 more source