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.
266 related articles for article (PubMed ID: 34529029)
1. How much can deep learning improve prediction of the responses to drugs in cancer cell lines? Chen Y; Zhang L Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34529029 [TBL] [Abstract][Full Text] [Related]
2. Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization. Wang L; Li X; Zhang L; Gao Q BMC Cancer; 2017 Aug; 17(1):513. PubMed ID: 28768489 [TBL] [Abstract][Full Text] [Related]
3. Hi-GeoMVP: a hierarchical geometry-enhanced deep learning model for drug response prediction. Chen Y; Zhang L Bioinformatics; 2024 Mar; 40(4):. PubMed ID: 38614131 [TBL] [Abstract][Full Text] [Related]
5. De novo Prediction of Cell-Drug Sensitivities Using Deep Learning-based Graph Regularized Matrix Factorization. Ren S; Tao Y; Yu K; Xue Y; Schwartz R; Lu X Pac Symp Biocomput; 2022; 27():278-289. PubMed ID: 34890156 [TBL] [Abstract][Full Text] [Related]
6. DeepDRK: a deep learning framework for drug repurposing through kernel-based multi-omics integration. Wang Y; Yang Y; Chen S; Wang J Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33822890 [TBL] [Abstract][Full Text] [Related]
7. Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer. Chereda H; Bleckmann A; Menck K; Perera-Bel J; Stegmaier P; Auer F; Kramer F; Leha A; Beißbarth T Genome Med; 2021 Mar; 13(1):42. PubMed ID: 33706810 [TBL] [Abstract][Full Text] [Related]
8. GraphCDR: a graph neural network method with contrastive learning for cancer drug response prediction. Liu X; Song C; Huang F; Fu H; Xiao W; Zhang W Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34727569 [TBL] [Abstract][Full Text] [Related]
9. DRN-CDR: A cancer drug response prediction model using multi-omics and drug features. Saranya KR; Vimina ER Comput Biol Chem; 2024 Oct; 112():108175. PubMed ID: 39191166 [TBL] [Abstract][Full Text] [Related]
10. A survey and systematic assessment of computational methods for drug response prediction. Chen J; Zhang L Brief Bioinform; 2021 Jan; 22(1):232-246. PubMed ID: 31927568 [TBL] [Abstract][Full Text] [Related]
11. Improving anti-cancer drug response prediction using multi-task learning on graph convolutional networks. Liu H; Peng W; Dai W; Lin J; Fu X; Liu L; Liu L; Yu N Methods; 2024 Feb; 222():41-50. PubMed ID: 38157919 [TBL] [Abstract][Full Text] [Related]
12. TGSA: protein-protein association-based twin graph neural networks for drug response prediction with similarity augmentation. Zhu Y; Ouyang Z; Chen W; Feng R; Chen DZ; Cao J; Wu J Bioinformatics; 2022 Jan; 38(2):461-468. PubMed ID: 34559177 [TBL] [Abstract][Full Text] [Related]
13. DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction. Liu H; Wang F; Yu J; Pan Y; Gong C; Zhang L; Zhang L PLoS Comput Biol; 2024 Apr; 20(4):e1012012. PubMed ID: 38574114 [TBL] [Abstract][Full Text] [Related]
14. GADRP: graph convolutional networks and autoencoders for cancer drug response prediction. Wang H; Dai C; Wen Y; Wang X; Liu W; He S; Bo X; Peng S Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36460622 [TBL] [Abstract][Full Text] [Related]
15. 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]
16. Deep learning and multi-omics approach to predict drug responses in cancer. Wang C; Lye X; Kaalia R; Kumar P; Rajapakse JC BMC Bioinformatics; 2022 Nov; 22(Suppl 10):632. PubMed ID: 36443676 [TBL] [Abstract][Full Text] [Related]
17. MOLI: multi-omics late integration with deep neural networks for drug response prediction. Sharifi-Noghabi H; Zolotareva O; Collins CC; Ester M Bioinformatics; 2019 Jul; 35(14):i501-i509. PubMed ID: 31510700 [TBL] [Abstract][Full Text] [Related]
18. DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics. Sharma A; Lysenko A; Boroevich KA; Tsunoda T Sci Rep; 2023 Feb; 13(1):2483. PubMed ID: 36774402 [TBL] [Abstract][Full Text] [Related]
19. GPDRP: a multimodal framework for drug response prediction with graph transformer. Yang Y; Li P BMC Bioinformatics; 2023 Dec; 24(1):484. PubMed ID: 38105227 [TBL] [Abstract][Full Text] [Related]
20. TransCDR: a deep learning model for enhancing the generalizability of drug activity prediction through transfer learning and multimodal data fusion. Xia X; Zhu C; Zhong F; Liu L BMC Biol; 2024 Oct; 22(1):227. PubMed ID: 39385185 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]