154 related articles for article (PubMed ID: 38461284)
1. DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies.
Lao C; Zheng P; Chen H; Liu Q; An F; Li Z
BMC Bioinformatics; 2024 Mar; 25(1):105. PubMed ID: 38461284
[TBL] [Abstract][Full Text] [Related]
2. DeepCDR: a hybrid graph convolutional network for predicting cancer drug response.
Liu Q; Hu Z; Jiang R; Zhou M
Bioinformatics; 2020 Dec; 36(Suppl_2):i911-i918. PubMed ID: 33381841
[TBL] [Abstract][Full Text] [Related]
3. DeepTTA: a transformer-based model for predicting cancer drug response.
Jiang L; Jiang C; Yu X; Fu R; Jin S; Liu X
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35348595
[TBL] [Abstract][Full Text] [Related]
4. Predicting anticancer hyperfoods with graph convolutional networks.
Gonzalez G; Gong S; Laponogov I; Bronstein M; Veselkov K
Hum Genomics; 2021 Jun; 15(1):33. PubMed ID: 34099048
[TBL] [Abstract][Full Text] [Related]
5. Predicting cancer drug response using parallel heterogeneous graph convolutional networks with neighborhood interactions.
Peng W; Liu H; Dai W; Yu N; Wang J
Bioinformatics; 2022 Sep; 38(19):4546-4553. PubMed ID: 35997568
[TBL] [Abstract][Full Text] [Related]
6. DualGCN: a dual graph convolutional network model to predict cancer drug response.
Ma T; Liu Q; Li H; Zhou M; Jiang R; Zhang X
BMC Bioinformatics; 2022 Apr; 23(Suppl 4):129. PubMed ID: 35428192
[TBL] [Abstract][Full Text] [Related]
7. Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network.
Liu P; Li H; Li S; Leung KS
BMC Bioinformatics; 2019 Jul; 20(1):408. PubMed ID: 31357929
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. ITNR: Inversion Transformer-based Neural Ranking for cancer drug recommendations.
Sotudian S; Paschalidis IC
Comput Biol Med; 2024 Apr; 172():108312. PubMed ID: 38503090
[TBL] [Abstract][Full Text] [Related]
10. A link prediction approach to cancer drug sensitivity prediction.
Turki T; Wei Z
BMC Syst Biol; 2017 Oct; 11(Suppl 5):94. PubMed ID: 28984192
[TBL] [Abstract][Full Text] [Related]
11. SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures.
Zuo Z; Wang P; Chen X; Tian L; Ge H; Qian D
BMC Bioinformatics; 2021 Sep; 22(1):434. PubMed ID: 34507532
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. XGraphCDS: An explainable deep learning model for predicting drug sensitivity from gene pathways and chemical structures.
Wang Y; Yu X; Gu Y; Li W; Zhu K; Chen L; Tang Y; Liu G
Comput Biol Med; 2024 Jan; 168():107746. PubMed ID: 38039896
[TBL] [Abstract][Full Text] [Related]
14. MMCL-CDR: enhancing cancer drug response prediction with multi-omics and morphology images contrastive representation learning.
Li Y; Guo Z; Gao X; Wang G
Bioinformatics; 2023 Dec; 39(12):. PubMed ID: 38070154
[TBL] [Abstract][Full Text] [Related]
15. Gene-centric multi-omics integration with convolutional encoders for cancer drug response prediction.
Lee M; Kim PJ; Joe H; Kim HG
Comput Biol Med; 2022 Dec; 151(Pt A):106192. PubMed ID: 36327883
[TBL] [Abstract][Full Text] [Related]
16. Fusing graph transformer with multi-aggregate GCN for enhanced drug-disease associations prediction.
He S; Yun L; Yi H
BMC Bioinformatics; 2024 Feb; 25(1):79. PubMed ID: 38378479
[TBL] [Abstract][Full Text] [Related]
17. Predicting Drug Response Based on Multi-Omics Fusion and Graph Convolution.
Peng W; Chen T; Dai W
IEEE J Biomed Health Inform; 2022 Mar; 26(3):1384-1393. PubMed ID: 34347616
[TBL] [Abstract][Full Text] [Related]
18. DROEG: a method for cancer drug response prediction based on omics and essential genes integration.
Wu P; Sun R; Fahira A; Chen Y; Jiangzhou H; Wang K; Yang Q; Dai Y; Pan D; Shi Y; Wang Z
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36715269
[TBL] [Abstract][Full Text] [Related]
19. The prediction of drug sensitivity by multi-omics fusion reveals the heterogeneity of drug response in pan-cancer.
Wang C; Zhang M; Zhao J; Li B; Xiao X; Zhang Y
Comput Biol Med; 2023 Sep; 163():107220. PubMed ID: 37406589
[TBL] [Abstract][Full Text] [Related]
20. Drug-target affinity prediction with extended graph learning-convolutional networks.
Qi H; Yu T; Yu W; Liu C
BMC Bioinformatics; 2024 Feb; 25(1):75. PubMed ID: 38365583
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]