354 related articles for article (PubMed ID: 30704458)
1. Predicting drug response of tumors from integrated genomic profiles by deep neural networks.
Chiu YC; Chen HH; Zhang T; Zhang S; Gorthi A; Wang LJ; Huang Y; Chen Y
BMC Med Genomics; 2019 Jan; 12(Suppl 1):18. PubMed ID: 30704458
[TBL] [Abstract][Full Text] [Related]
2. Predicting breast cancer drug response using a multiple-layer cell line drug response network model.
Huang S; Hu P; Lakowski TM
BMC Cancer; 2021 May; 21(1):648. PubMed ID: 34059012
[TBL] [Abstract][Full Text] [Related]
3. DeepDSC: A Deep Learning Method to Predict Drug Sensitivity of Cancer Cell Lines.
Li M; Wang Y; Zheng R; Shi X; Li Y; Wu FX; Wang J
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):575-582. PubMed ID: 31150344
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning.
Pang W; Chen M; Qin Y
BMC Bioinformatics; 2024 May; 25(1):182. PubMed ID: 38724920
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. kESVR: An Ensemble Model for Drug Response Prediction in Precision Medicine Using Cancer Cell Lines Gene Expression.
Majumdar A; Liu Y; Lu Y; Wu S; Cheng L
Genes (Basel); 2021 May; 12(6):. PubMed ID: 34070793
[TBL] [Abstract][Full Text] [Related]
8. Predicting drug activity against cancer through genomic profiles and SMILES.
Abbasi M; Carvalho FG; Ribeiro B; Arrais JP
Artif Intell Med; 2024 Apr; 150():102820. PubMed ID: 38553160
[TBL] [Abstract][Full Text] [Related]
9. A performance evaluation of drug response prediction models for individual drugs.
Park A; Lee Y; Nam S
Sci Rep; 2023 Jul; 13(1):11911. PubMed ID: 37488424
[TBL] [Abstract][Full Text] [Related]
10. Predicting drug response through tumor deconvolution by cancer cell lines.
Hsu YC; Chiu YC; Lu TP; Hsiao TH; Chen Y
Patterns (N Y); 2024 Apr; 5(4):100949. PubMed ID: 38645769
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Predicting and characterizing a cancer dependency map of tumors with deep learning.
Chiu YC; Zheng S; Wang LJ; Iskra BS; Rao MK; Houghton PJ; Huang Y; Chen Y
Sci Adv; 2021 Aug; 7(34):. PubMed ID: 34417181
[TBL] [Abstract][Full Text] [Related]
13. A Deep Learning Model for Cell Growth Inhibition IC50 Prediction and Its Application for Gastric Cancer Patients.
Joo M; Park A; Kim K; Son WJ; Lee HS; Lim G; Lee J; Lee DH; An J; Kim JH; Ahn T; Nam S
Int J Mol Sci; 2019 Dec; 20(24):. PubMed ID: 31842404
[TBL] [Abstract][Full Text] [Related]
14. shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning.
Wang LJ; Ning M; Nayak T; Kasper MJ; Monga SP; Huang Y; Chen Y; Chiu YC
Patterns (N Y); 2024 Feb; 5(2):100894. PubMed ID: 38370127
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. 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]
18. 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]
19. Opening up the blackbox: an interpretable deep neural network-based classifier for cell-type specific enhancer predictions.
Kim SG; Theera-Ampornpunt N; Fang CH; Harwani M; Grama A; Chaterji S
BMC Syst Biol; 2016 Aug; 10 Suppl 2(Suppl 2):54. PubMed ID: 27490187
[TBL] [Abstract][Full Text] [Related]
20. Super.FELT: supervised feature extraction learning using triplet loss for drug response prediction with multi-omics data.
Park S; Soh J; Lee H
BMC Bioinformatics; 2021 May; 22(1):269. PubMed ID: 34034645
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
