BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

191 related articles for article (PubMed ID: 33173014)

  • 1. H-RACS: a handy tool to rank anti-cancer synergistic drugs.
    Yan X; Yang Y; Chen Z; Yin Z; Deng Z; Qiu T; Tang K; Cao Z
    Aging (Albany NY); 2020 Nov; 12(21):21504-21517. PubMed ID: 33173014
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An integrated framework for identification of effective and synergistic anti-cancer drug combinations.
    Sharma A; Rani R
    J Bioinform Comput Biol; 2018 Oct; 16(5):1850017. PubMed ID: 30304987
    [TBL] [Abstract][Full Text] [Related]  

  • 3. SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.
    Huangfu X; Zhang C; Li H; Li S; Li Y
    Comput Biol Chem; 2024 Jun; 110():108054. PubMed ID: 38522389
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DeepSynergy: predicting anti-cancer drug synergy with Deep Learning.
    Preuer K; Lewis RPI; Hochreiter S; Bender A; Bulusu KC; Klambauer G
    Bioinformatics; 2018 May; 34(9):1538-1546. PubMed ID: 29253077
    [TBL] [Abstract][Full Text] [Related]  

  • 5. In silico drug combination discovery for personalized cancer therapy.
    Jeon M; Kim S; Park S; Lee H; Kang J
    BMC Syst Biol; 2018 Mar; 12(Suppl 2):16. PubMed ID: 29560824
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles.
    Li X; Xu Y; Cui H; Huang T; Wang D; Lian B; Li W; Qin G; Chen L; Xie L
    Artif Intell Med; 2017 Nov; 83():35-43. PubMed ID: 28583437
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Combining genomic and network characteristics for extended capability in predicting synergistic drugs for cancer.
    Sun Y; Sheng Z; Ma C; Tang K; Zhu R; Wu Z; Shen R; Feng J; Wu D; Huang D; Huang D; Fei J; Liu Q; Cao Z
    Nat Commun; 2015 Sep; 6():8481. PubMed ID: 26412466
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Network Propagation Predicts Drug Synergy in Cancers.
    Li H; Li T; Quang D; Guan Y
    Cancer Res; 2018 Sep; 78(18):5446-5457. PubMed ID: 30054332
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A review of machine learning approaches for drug synergy prediction in cancer.
    Torkamannia A; Omidi Y; Ferdousi R
    Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35323854
    [TBL] [Abstract][Full Text] [Related]  

  • 10. In-silico Prediction of Synergistic Anti-Cancer Drug Combinations Using Multi-omics Data.
    Celebi R; Bear Don't Walk O; Movva R; Alpsoy S; Dumontier M
    Sci Rep; 2019 Jun; 9(1):8949. PubMed ID: 31222109
    [TBL] [Abstract][Full Text] [Related]  

  • 11. DrugCombDB: a comprehensive database of drug combinations toward the discovery of combinatorial therapy.
    Liu H; Zhang W; Zou B; Wang J; Deng Y; Deng L
    Nucleic Acids Res; 2020 Jan; 48(D1):D871-D881. PubMed ID: 31665429
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs.
    Abd El-Hafeez T; Shams MY; Elshaier YAMM; Farghaly HM; Hassanien AE
    Sci Rep; 2024 Jan; 14(1):2428. PubMed ID: 38287066
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predict effective drug combination by deep belief network and ontology fingerprints.
    Chen G; Tsoi A; Xu H; Zheng WJ
    J Biomed Inform; 2018 Sep; 85():149-154. PubMed ID: 30081101
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models.
    Zhang T; Zhang L; Payne PRO; Li F
    Methods Mol Biol; 2021; 2194():223-238. PubMed ID: 32926369
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Drug Selection via Joint Push and Learning to Rank.
    He Y; Liu J; Ning X
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(1):110-123. PubMed ID: 29994481
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting drug synergy for precision medicine using network biology and machine learning.
    Cuvitoglu A; Zhou JX; Huang S; Isik Z
    J Bioinform Comput Biol; 2019 Apr; 17(2):1950012. PubMed ID: 31057072
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Statistical assessment and visualization of synergies for large-scale sparse drug combination datasets.
    Amzallag A; Ramaswamy S; Benes CH
    BMC Bioinformatics; 2019 Feb; 20(1):83. PubMed ID: 30777010
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A novel approach to predicting the synergy of anti-cancer drug combinations using document-based feature extraction.
    Shim Y; Lee M; Kim PJ; Kim HG
    BMC Bioinformatics; 2022 May; 23(1):163. PubMed ID: 35513784
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 10.