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.
3. Genomics of drug sensitivity in bladder cancer: an integrated resource for pharmacogenomic analysis in bladder cancer. Ansari AA; Park I; Kim I; Park S; Ahn SM; Lee JL BMC Med Genomics; 2018 Oct; 11(1):88. PubMed ID: 30285760 [TBL] [Abstract][Full Text] [Related]
4. GDA, a web-based tool for Genomics and Drugs integrated analysis. Caroli J; Sorrentino G; Forcato M; Del Sal G; Bicciato S Nucleic Acids Res; 2018 Jul; 46(W1):W148-W156. PubMed ID: 29800349 [TBL] [Abstract][Full Text] [Related]
5. Integrating heterogeneous drug sensitivity data from cancer pharmacogenomic studies. Pozdeyev N; Yoo M; Mackie R; Schweppe RE; Tan AC; Haugen BR Oncotarget; 2016 Aug; 7(32):51619-51625. PubMed ID: 27322211 [TBL] [Abstract][Full Text] [Related]
6. 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]
7. COSMIC (the Catalogue of Somatic Mutations in Cancer): a resource to investigate acquired mutations in human cancer. Forbes SA; Tang G; Bindal N; Bamford S; Dawson E; Cole C; Kok CY; Jia M; Ewing R; Menzies A; Teague JW; Stratton MR; Futreal PA Nucleic Acids Res; 2010 Jan; 38(Database issue):D652-7. PubMed ID: 19906727 [TBL] [Abstract][Full Text] [Related]
8. PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data. Piñeiro-Yáñez E; Reboiro-Jato M; Gómez-López G; Perales-Patón J; Troulé K; Rodríguez JM; Tejero H; Shimamura T; López-Casas PP; Carretero J; Valencia A; Hidalgo M; Glez-Peña D; Al-Shahrour F Genome Med; 2018 May; 10(1):41. PubMed ID: 29848362 [TBL] [Abstract][Full Text] [Related]
9. Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets. Dwane L; Behan FM; Gonçalves E; Lightfoot H; Yang W; van der Meer D; Shepherd R; Pignatelli M; Iorio F; Garnett MJ Nucleic Acids Res; 2021 Jan; 49(D1):D1365-D1372. PubMed ID: 33068406 [TBL] [Abstract][Full Text] [Related]
10. Current Trends in Drug Sensitivity Prediction. Cortes-Ciriano I; Mervin LH; Bender A Curr Pharm Des; 2016; 22(46):6918-6927. PubMed ID: 27784247 [TBL] [Abstract][Full Text] [Related]
11. Evaluating the consistency of large-scale pharmacogenomic studies. Rahman R; Dhruba SR; Matlock K; De-Niz C; Ghosh S; Pal R Brief Bioinform; 2019 Sep; 20(5):1734-1753. PubMed ID: 31846027 [TBL] [Abstract][Full Text] [Related]
12. Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia. Covell DG PLoS One; 2015; 10(7):e0127433. PubMed ID: 26132924 [TBL] [Abstract][Full Text] [Related]
13. ccmGDB: a database for cancer cell metabolism genes. Kim P; Cheng F; Zhao J; Zhao Z Nucleic Acids Res; 2016 Jan; 44(D1):D959-68. PubMed ID: 26519468 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Interactive webtool for analyzing drug sensitivity and resistance associated with genetic signatures of cancer cell lines. Boeschen M; Le Duc D; Stiller M; von Laffert M; Schöneberg T; Horn S J Cancer Res Clin Oncol; 2023 Aug; 149(9):5539-5545. PubMed ID: 36472769 [TBL] [Abstract][Full Text] [Related]
17. Two-step multi-omics modelling of drug sensitivity in cancer cell lines to identify driving mechanisms. Kusch N; Schuppert A PLoS One; 2020; 15(11):e0238961. PubMed ID: 33226984 [TBL] [Abstract][Full Text] [Related]
18. 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]
19. Using drug response data to identify molecular effectors, and molecular "omic" data to identify candidate drugs in cancer. Reinhold WC; Varma S; Rajapakse VN; Luna A; Sousa FG; Kohn KW; Pommier YG Hum Genet; 2015 Jan; 134(1):3-11. PubMed ID: 25213708 [TBL] [Abstract][Full Text] [Related]
20. CPADS: a web tool for comprehensive pancancer analysis of drug sensitivity. Li K; Yang H; Lin A; Xie J; Wang H; Zhou J; Carr SR; Liu Z; Li X; Zhang J; Cheng Q; Schrump DS; Luo P; Wei T Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38770717 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]