600 related articles for article (PubMed ID: 34571537)
1. DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations.
Wang J; Liu X; Shen S; Deng L; Liu H
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34571537
[TBL] [Abstract][Full Text] [Related]
2. Predicting synergistic anticancer drug combination based on low-rank global attention mechanism and bilinear predictor.
Gan Y; Huang X; Guo W; Yan C; Zou G
Bioinformatics; 2023 Oct; 39(10):. PubMed ID: 37812255
[TBL] [Abstract][Full Text] [Related]
3. TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations.
Liu Q; Xie L
PLoS Comput Biol; 2021 Feb; 17(2):e1008653. PubMed ID: 33577560
[TBL] [Abstract][Full Text] [Related]
4. AttenSyn: An Attention-Based Deep Graph Neural Network for Anticancer Synergistic Drug Combination Prediction.
Wang T; Wang R; Wei L
J Chem Inf Model; 2024 Apr; 64(7):2854-2862. PubMed ID: 37565997
[TBL] [Abstract][Full Text] [Related]
5. MFSynDCP: multi-source feature collaborative interactive learning for drug combination synergy prediction.
Dong Y; Chang Y; Wang Y; Han Q; Wen X; Yang Z; Zhang Y; Qiang Y; Wu K; Fan X; Ren X
BMC Bioinformatics; 2024 Apr; 25(1):140. PubMed ID: 38561679
[TBL] [Abstract][Full Text] [Related]
6. A complete graph-based approach with multi-task learning for predicting synergistic drug combinations.
Wang X; Zhu H; Chen D; Yu Y; Liu Q; Liu Q
Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37261842
[TBL] [Abstract][Full Text] [Related]
7. DTF: Deep Tensor Factorization for predicting anticancer drug synergy.
Sun Z; Huang S; Jiang P; Hu P
Bioinformatics; 2020 Aug; 36(16):4483-4489. PubMed ID: 32369563
[TBL] [Abstract][Full Text] [Related]
8. PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network.
Wang X; Zhu H; Jiang Y; Li Y; Tang C; Chen X; Li Y; Liu Q; Liu Q
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35043159
[TBL] [Abstract][Full Text] [Related]
9. Network-principled deep generative models for designing drug combinations as graph sets.
Karimi M; Hasanzadeh A; Shen Y
Bioinformatics; 2020 Jul; 36(Suppl_1):i445-i454. PubMed ID: 32657357
[TBL] [Abstract][Full Text] [Related]
10. Predicting Drug Synergy and Discovering New Drug Combinations Based on a Graph Autoencoder and Convolutional Neural Network.
Li H; Zou L; Kowah JAH; He D; Wang L; Yuan M; Liu X
Interdiscip Sci; 2023 Jun; 15(2):316-330. PubMed ID: 36943614
[TBL] [Abstract][Full Text] [Related]
11. MGAE-DC: Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders.
Zhang P; Tu S
PLoS Comput Biol; 2023 Mar; 19(3):e1010951. PubMed ID: 36867661
[TBL] [Abstract][Full Text] [Related]
12. DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations.
Hu J; Gao J; Fang X; Liu Z; Wang F; Huang W; Wu H; Zhao G
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35915050
[TBL] [Abstract][Full Text] [Related]
13. Deep graph embedding for prioritizing synergistic anticancer drug combinations.
Jiang P; Huang S; Fu Z; Sun Z; Lakowski TM; Hu P
Comput Struct Biotechnol J; 2020; 18():427-438. PubMed ID: 32153729
[TBL] [Abstract][Full Text] [Related]
14. Network-based drug sensitivity prediction.
Ahmed KT; Park S; Jiang Q; Yeu Y; Hwang T; Zhang W
BMC Med Genomics; 2020 Dec; 13(Suppl 11):193. PubMed ID: 33371891
[TBL] [Abstract][Full Text] [Related]
15. BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction.
Li M; Lu Z; Wu Y; Li Y
Bioinformatics; 2022 Mar; 38(7):1995-2002. PubMed ID: 35043942
[TBL] [Abstract][Full Text] [Related]
16. [Synergistic drug combination prediction in multi-input neural network].
Chen X; Qin Y; Chen M; Zhang C
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2020 Aug; 37(4):676-682. PubMed ID: 32840085
[TBL] [Abstract][Full Text] [Related]
17. HiGNN: A Hierarchical Informative Graph Neural Network for Molecular Property Prediction Equipped with Feature-Wise Attention.
Zhu W; Zhang Y; Zhao D; Xu J; Wang L
J Chem Inf Model; 2023 Jan; 63(1):43-55. PubMed ID: 36519623
[TBL] [Abstract][Full Text] [Related]
18. Ensemble Prediction of Synergistic Drug Combinations Incorporating Biological, Chemical, Pharmacological, and Network Knowledge.
Ding P; Yin R; Luo J; Kwoh CK
IEEE J Biomed Health Inform; 2019 May; 23(3):1336-1345. PubMed ID: 29994408
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. MMSyn: A New Multimodal Deep Learning Framework for Enhanced Prediction of Synergistic Drug Combinations.
Pang Y; Chen Y; Lin M; Zhang Y; Zhang J; Wang L
J Chem Inf Model; 2024 May; 64(9):3689-3705. PubMed ID: 38676916
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
