151 related articles for article (PubMed ID: 35625486)
1. BioChemDDI: Predicting Drug-Drug Interactions by Fusing Biochemical and Structural Information through a Self-Attention Mechanism.
Ren ZH; Yu CQ; Li LP; You ZH; Pan J; Guan YJ; Guo LX
Biology (Basel); 2022 May; 11(5):. PubMed ID: 35625486
[TBL] [Abstract][Full Text] [Related]
2. A biomedical knowledge graph-based method for drug-drug interactions prediction through combining local and global features with deep neural networks.
Ren ZH; You ZH; Yu CQ; Li LP; Guan YJ; Guo LX; Pan J
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36070624
[TBL] [Abstract][Full Text] [Related]
3. BioDKG-DDI: predicting drug-drug interactions based on drug knowledge graph fusing biochemical information.
Ren ZH; Yu CQ; Li LP; You ZH; Guan YJ; Wang XF; Pan J
Brief Funct Genomics; 2022 May; 21(3):216-229. PubMed ID: 35368060
[TBL] [Abstract][Full Text] [Related]
4. DPDDI: a deep predictor for drug-drug interactions.
Feng YH; Zhang SW; Shi JY
BMC Bioinformatics; 2020 Sep; 21(1):419. PubMed ID: 32972364
[TBL] [Abstract][Full Text] [Related]
5. DMFDDI: deep multimodal fusion for drug-drug interaction prediction.
Gan Y; Liu W; Xu G; Yan C; Zou G
Brief Bioinform; 2023 Sep; 24(6):. PubMed ID: 37930025
[TBL] [Abstract][Full Text] [Related]
6. Multi-type feature fusion based on graph neural network for drug-drug interaction prediction.
He C; Liu Y; Li H; Zhang H; Mao Y; Qin X; Liu L; Zhang X
BMC Bioinformatics; 2022 Jun; 23(1):224. PubMed ID: 35689200
[TBL] [Abstract][Full Text] [Related]
7. Multi-view feature representation and fusion for drug-drug interactions prediction.
Wang J; Zhang S; Li R; Chen G; Yan S; Ma L
BMC Bioinformatics; 2023 Mar; 24(1):93. PubMed ID: 36918766
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. DeepMPF: deep learning framework for predicting drug-target interactions based on multi-modal representation with meta-path semantic analysis.
Ren ZH; You ZH; Zou Q; Yu CQ; Ma YF; Guan YJ; You HR; Wang XF; Pan J
J Transl Med; 2023 Jan; 21(1):48. PubMed ID: 36698208
[TBL] [Abstract][Full Text] [Related]
10. Predicting drug-drug interactions by graph convolutional network with multi-kernel.
Wang F; Lei X; Liao B; Wu FX
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34864856
[TBL] [Abstract][Full Text] [Related]
11. Improving drug-drug interactions prediction with interpretability via meta-path-based information fusion.
Zhao W; Yuan X; Shen X; Jiang X; Shi C; He T; Hu X
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36750041
[TBL] [Abstract][Full Text] [Related]
12. MCFF-MTDDI: multi-channel feature fusion for multi-typed drug-drug interaction prediction.
Han CD; Wang CC; Huang L; Chen X
Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37291761
[TBL] [Abstract][Full Text] [Related]
13. Predicting drug-drug interactions based on multi-view and multichannel attention deep learning.
Huang L; Chen Q; Lan W
Health Inf Sci Syst; 2023 Dec; 11(1):50. PubMed ID: 37941825
[TBL] [Abstract][Full Text] [Related]
14. Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association prediction.
Zhang H; Cui H; Zhang T; Cao Y; Xuan P
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35136910
[TBL] [Abstract][Full Text] [Related]
15. Prediction of Drug-Drug Interaction Using an Attention-Based Graph Neural Network on Drug Molecular Graphs.
Feng YH; Zhang SW
Molecules; 2022 May; 27(9):. PubMed ID: 35566354
[TBL] [Abstract][Full Text] [Related]
16. Predicting drug-target interaction network using deep learning model.
You J; McLeod RD; Hu P
Comput Biol Chem; 2019 Jun; 80():90-101. PubMed ID: 30939415
[TBL] [Abstract][Full Text] [Related]
17. Molormer: a lightweight self-attention-based method focused on spatial structure of molecular graph for drug-drug interactions prediction.
Zhang X; Wang G; Meng X; Wang S; Zhang Y; Rodriguez-Paton A; Wang J; Wang X
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35849817
[TBL] [Abstract][Full Text] [Related]
18. Prediction of the Drug-Drug Interaction Types with the Unified Embedding Features from Drug Similarity Networks.
Yan XY; Yin PW; Wu XM; Han JX
Front Pharmacol; 2021; 12():794205. PubMed ID: 34987405
[TBL] [Abstract][Full Text] [Related]
19. GCNCDA: A new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm.
Wang L; You ZH; Li YM; Zheng K; Huang YA
PLoS Comput Biol; 2020 May; 16(5):e1007568. PubMed ID: 32433655
[TBL] [Abstract][Full Text] [Related]
20. GVDTI: graph convolutional and variational autoencoders with attribute-level attention for drug-protein interaction prediction.
Xuan P; Fan M; Cui H; Zhang T; Nakaguchi T
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34718408
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
