These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
140 related articles for article (PubMed ID: 38710353)
21. Identifying circRNA-disease association based on relational graph attention network and hypergraph attention network. Lu P; Wu J; Zhang W Anal Biochem; 2024 Nov; 694():115628. PubMed ID: 39069246 [TBL] [Abstract][Full Text] [Related]
22. THGNCDA: circRNA-disease association prediction based on triple heterogeneous graph network. Guo Y; Yi M Brief Funct Genomics; 2024 Jul; 23(4):384-394. PubMed ID: 37738503 [TBL] [Abstract][Full Text] [Related]
23. LGCDA: Predicting CircRNA-Disease Association Based on Fusion of Local and Global Features. Lan W; Li C; Chen Q; Yu N; Pan Y; Zheng Y; Chen YP IEEE/ACM Trans Comput Biol Bioinform; 2024; 21(5):1413-1422. PubMed ID: 38607720 [TBL] [Abstract][Full Text] [Related]
24. Prediction of circRNA-MiRNA Association Using Singular Value Decomposition and Graph Neural Networks. Qian Y; Zheng J; Jiang Y; Li S; Deng L IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3461-3468. PubMed ID: 36395130 [TBL] [Abstract][Full Text] [Related]
25. Meta-Path Semantic and Global-Local Representation Learning Enhanced Graph Convolutional Model for Disease-Related miRNA Prediction. Xuan P; Wang X; Cui H; Meng X; Nakaguchi T; Zhang T IEEE J Biomed Health Inform; 2024 Jul; 28(7):4306-4316. PubMed ID: 38709611 [TBL] [Abstract][Full Text] [Related]
26. PGCNMDA: Learning node representations along paths with graph convolutional network for predicting miRNA-disease associations. Chu S; Duan G; Yan C Methods; 2024 Sep; 229():71-81. PubMed ID: 38909974 [TBL] [Abstract][Full Text] [Related]
27. Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations. Guo LX; Wang L; You ZH; Yu CQ; Hu ML; Zhao BW; Li Y Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38324624 [TBL] [Abstract][Full Text] [Related]
28. Predicting the potential associations between circRNA and drug sensitivity using a multisource feature-based approach. Yin S; Xu P; Jiang Y; Yang X; Lin Y; Zheng M; Hu J; Zhao Q J Cell Mol Med; 2024 Oct; 28(19):e18591. PubMed ID: 39347936 [TBL] [Abstract][Full Text] [Related]
29. KGANCDA: predicting circRNA-disease associations based on knowledge graph attention network. Lan W; Dong Y; Chen Q; Zheng R; Liu J; Pan Y; Chen YP Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34864877 [TBL] [Abstract][Full Text] [Related]
30. DCDA: CircRNA-Disease Association Prediction with Feed-Forward Neural Network and Deep Autoencoder. Turgut H; Turanli B; Boz B Interdiscip Sci; 2024 Mar; 16(1):91-103. PubMed ID: 37978116 [TBL] [Abstract][Full Text] [Related]
31. Identifying Associations between Small Nucleolar RNAs and Diseases via Graph Convolutional Network and Attention Mechanism. Liu S; Zhu W; Wang P; Yu S; Wu F IEEE J Biomed Health Inform; 2024 Jul; PP():. PubMed ID: 38980776 [TBL] [Abstract][Full Text] [Related]
32. DPMGCDA: Deciphering circRNA-Drug Sensitivity Associations with Dual Perspective Learning and Path-Masked Graph Autoencoder. Luo Y; Deng L J Chem Inf Model; 2024 May; 64(10):4359-4372. PubMed ID: 38745420 [TBL] [Abstract][Full Text] [Related]
33. MNMDCDA: prediction of circRNA-disease associations by learning mixed neighborhood information from multiple distances. Li Y; Hu XG; Wang L; Li PP; You ZH Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36384071 [TBL] [Abstract][Full Text] [Related]
34. CDA-SKAG: Predicting circRNA-disease associations using similarity kernel fusion and an attention-enhancing graph autoencoder. Wang H; Han J; Li H; Duan L; Liu Z; Cheng H Math Biosci Eng; 2023 Feb; 20(5):7957-7980. PubMed ID: 37161181 [TBL] [Abstract][Full Text] [Related]
35. An efficient approach based on multi-sources information to predict circRNA-disease associations using deep convolutional neural network. Wang L; You ZH; Huang YA; Huang DS; Chan KCC Bioinformatics; 2020 Jul; 36(13):4038-4046. PubMed ID: 31793982 [TBL] [Abstract][Full Text] [Related]
36. GEHGAN: CircRNA-disease association prediction via graph embedding and heterogeneous graph attention network. Wang Y; Lu P Comput Biol Chem; 2024 Jun; 110():108079. PubMed ID: 38704917 [TBL] [Abstract][Full Text] [Related]
37. Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery. Zhang Y; Li X J Chem Inf Model; 2024 Apr; 64(8):3537-3547. PubMed ID: 38523272 [TBL] [Abstract][Full Text] [Related]
38. SGANRDA: semi-supervised generative adversarial networks for predicting circRNA-disease associations. Wang L; Yan X; You ZH; Zhou X; Li HY; Huang YA Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33734296 [TBL] [Abstract][Full Text] [Related]
39. iGRLCDA: identifying circRNA-disease association based on graph representation learning. Zhang HY; Wang L; You ZH; Hu L; Zhao BW; Li ZW; Li YM Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35323894 [TBL] [Abstract][Full Text] [Related]