Results 221 to 230 of about 106,924 (261)

DyGAT-FTNet: A Dynamic Graph Attention Network for Multi-Sensor Fault Diagnosis and Time-Frequency Data Fusion. [PDF]

Sensors (Basel)
Duan H, Chen G, Yu Y, Du C, Bao Z, Ma D.
europepmc   +1 more source

Tumor‐Derived Alpha‐1 Antitrypsin Promotes Liver Metastasis of Colorectal Cancer Through the Neutrophil Extracellular Traps–CCDC25 Pathway

Advanced Science, EarlyView.
ABSTRACT Liver metastasis is a leading cause of mortality in colorectal cancer (CRC), where the inflammatory tumor microenvironment, specifically neutrophil infiltration, significantly promotes metastatic colonization. This study reveals a pro‐metastatic role for alpha‐1 antitrypsin (A1AT) in CRC liver metastasis via a dual mechanism involving ...
Qian Fei, Chunning Li, Lei Zhan, Xiaoyan Li, Yan Hui, Yue Jin, Jing Zhang, Lu Yang, Xin Sun, Xiaoxi Li, Qian Dong, Jingdong Zhang   +11 more
wiley   +1 more source

DMGAT: predicting ncRNA-drug resistance associations based on diffusion map and heterogeneous graph attention network. [PDF]

Brief Bioinform
Liu T, Chen Q, Liu R, Sun Y, Wang Y, Zhu Y, Zhao T.   +6 more
europepmc   +1 more source

Multi-view united transformer block of graph attention network based autism spectrum disorder recognition. [PDF]

Front Psychiatry
Jemima DD, Selvarani AG, Lovenia JDL.
europepmc   +1 more source

MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction. [PDF]

BMC Bioinformatics
Saeed D, Xing H, AlBadani B, Feng L, Al-Sabri R, Abdullah M, Rehman A.   +6 more
europepmc   +1 more source

SpaCcLink: exploring downstream signaling regulations with graph attention network for systematic inference of spatial cell-cell communication. [PDF]

BMC Biol
Liu J, Ma L, Ju F, Zhao C, Yu L.
europepmc   +1 more source

GAADE: identification spatially variable genes based on adaptive graph attention network. [PDF]

Brief Bioinform
Zhang T, Sun H, Wu Z, Zhao Z, Zhao X, Zhang H, Gao B, Wang G.   +7 more
europepmc   +1 more source

Graph attention network predicts drug-gene associations of matrix metalloproteinases 9-based host modulation in periodontitis.

J Indian Soc Periodontol
Arumuganainar D, Anegundi RV, Ganesh PR, Yadalam PK.   +3 more
europepmc   +1 more source