211 related articles for article (PubMed ID: 38166659)
1. GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations.
Yao D; Li B; Zhan X; Zhan X; Yu L
BMC Bioinformatics; 2024 Jan; 25(1):5. PubMed ID: 38166659
[TBL] [Abstract][Full Text] [Related]
2. Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction.
Li G; Bai P; Liang C; Luo J
BMC Genomics; 2024 Jan; 25(1):73. PubMed ID: 38233788
[TBL] [Abstract][Full Text] [Related]
3. Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease Associations.
Xuan P; Pan S; Zhang T; Liu Y; Sun H
Cells; 2019 Aug; 8(9):. PubMed ID: 31480350
[TBL] [Abstract][Full Text] [Related]
4. Prediction of lncRNA and disease associations based on residual graph convolutional networks with attention mechanism.
Wang S; Qiao J; Feng S
Sci Rep; 2024 Mar; 14(1):5185. PubMed ID: 38431702
[TBL] [Abstract][Full Text] [Related]
5. gGATLDA: lncRNA-disease association prediction based on graph-level graph attention network.
Wang L; Zhong C
BMC Bioinformatics; 2022 Jan; 23(1):11. PubMed ID: 34983363
[TBL] [Abstract][Full Text] [Related]
6. Predicting lncRNA-disease associations using multiple metapaths in hierarchical graph attention networks.
Yao D; Deng Y; Zhan X; Zhan X
BMC Bioinformatics; 2024 Jan; 25(1):46. PubMed ID: 38287236
[TBL] [Abstract][Full Text] [Related]
7. Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases.
Sheng N; Wang Y; Huang L; Gao L; Cao Y; Xie X; Fu Y
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37529914
[TBL] [Abstract][Full Text] [Related]
8. LDAformer: predicting lncRNA-disease associations based on topological feature extraction and Transformer encoder.
Zhou Y; Wang X; Yao L; Zhu M
Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36094081
[TBL] [Abstract][Full Text] [Related]
9. MAGCNSE: predicting lncRNA-disease associations using multi-view attention graph convolutional network and stacking ensemble model.
Liang Y; Zhang ZQ; Liu NN; Wu YN; Gu CL; Wang YL
BMC Bioinformatics; 2022 May; 23(1):189. PubMed ID: 35590258
[TBL] [Abstract][Full Text] [Related]
10. A random forest based computational model for predicting novel lncRNA-disease associations.
Yao D; Zhan X; Zhan X; Kwoh CK; Li P; Wang J
BMC Bioinformatics; 2020 Mar; 21(1):126. PubMed ID: 32216744
[TBL] [Abstract][Full Text] [Related]
11. Predicting binary, discrete and continued lncRNA-disease associations via a unified framework based on graph regression.
Shi JY; Huang H; Zhang YN; Long YX; Yiu SM
BMC Med Genomics; 2017 Dec; 10(Suppl 4):65. PubMed ID: 29322937
[TBL] [Abstract][Full Text] [Related]
12. LncRNA-disease association identification using graph auto-encoder and learning to rank.
Liang Q; Zhang W; Wu H; Liu B
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36545805
[TBL] [Abstract][Full Text] [Related]
13. GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest.
Wu QW; Xia JF; Ni JC; Zheng CH
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33415333
[TBL] [Abstract][Full Text] [Related]
14. Predicting lncRNA-disease associations based on heterogeneous graph convolutional generative adversarial network.
Lu Z; Zhong H; Tang L; Luo J; Zhou W; Liu L
PLoS Comput Biol; 2023 Nov; 19(11):e1011634. PubMed ID: 38019786
[TBL] [Abstract][Full Text] [Related]
15. Predicting miRNA-disease association from heterogeneous information network with GraRep embedding model.
Ji BY; You ZH; Cheng L; Zhou JR; Alghazzawi D; Li LP
Sci Rep; 2020 Apr; 10(1):6658. PubMed ID: 32313121
[TBL] [Abstract][Full Text] [Related]
16. LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.
Xuan P; Jia L; Zhang T; Sheng N; Li X; Li J
Int J Mol Sci; 2019 Sep; 20(18):. PubMed ID: 31510011
[TBL] [Abstract][Full Text] [Related]
17. CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA-Disease Associations.
Xuan P; Sheng N; Zhang T; Liu Y; Guo Y
Int J Mol Sci; 2019 Aug; 20(17):. PubMed ID: 31480319
[TBL] [Abstract][Full Text] [Related]
18. Specific topology and topological connection sensitivity enhanced graph learning for lncRNA-disease association prediction.
Xuan P; Bai H; Cui H; Zhang X; Nakaguchi T; Zhang T
Comput Biol Med; 2023 Sep; 164():107265. PubMed ID: 37531860
[TBL] [Abstract][Full Text] [Related]
19. Hierarchical graph attention network for miRNA-disease association prediction.
Li Z; Zhong T; Huang D; You ZH; Nie R
Mol Ther; 2022 Apr; 30(4):1775-1786. PubMed ID: 35121109
[TBL] [Abstract][Full Text] [Related]
20. EOESGC: predicting miRNA-disease associations based on embedding of embedding and simplified graph convolutional network.
Pang S; Zhuang Y; Wang X; Wang F; Qiao S
BMC Med Inform Decis Mak; 2021 Nov; 21(1):319. PubMed ID: 34789236
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]