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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

244 related articles for article (PubMed ID: 33040150)

  • 1. Anticancer drug synergy prediction in understudied tissues using transfer learning.
    Kim Y; Zheng S; Tang J; Jim Zheng W; Li Z; Jiang X
    J Am Med Inform Assoc; 2021 Jan; 28(1):42-51. PubMed ID: 33040150
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Predicting anticancer synergistic drug combinations based on multi-task learning.
    Chen D; Wang X; Zhu H; Jiang Y; Li Y; Liu Q; Liu Q
    BMC Bioinformatics; 2023 Nov; 24(1):448. PubMed ID: 38012551
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DTF: Deep Tensor Factorization for predicting anticancer drug synergy.
    Sun Z; Huang S; Jiang P; Hu P
    Bioinformatics; 2020 Aug; 36(16):4483-4489. PubMed ID: 32369563
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multi-way relation-enhanced hypergraph representation learning for anti-cancer drug synergy prediction.
    Liu X; Song C; Liu S; Li M; Zhou X; Zhang W
    Bioinformatics; 2022 Oct; 38(20):4782-4789. PubMed ID: 36000898
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. 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]  

  • 10. DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations.
    Wang J; Liu X; Shen S; Deng L; Liu H
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34571537
    [TBL] [Abstract][Full Text] [Related]  

  • 11. TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations.
    Liu Q; Xie L
    PLoS Comput Biol; 2021 Feb; 17(2):e1008653. PubMed ID: 33577560
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Prediction of anti-cancer drug synergy based on cross-matching network and cancer molecular subtypes.
    Su R; Han J; Sun C; Zhang D; Geng J; Wang P; Zeng X
    Comput Biol Med; 2024 Jun; 175():108441. PubMed ID: 38663353
    [TBL] [Abstract][Full Text] [Related]  

  • 14. SYNDEEP: a deep learning approach for the prediction of cancer drugs synergy.
    Torkamannia A; Omidi Y; Ferdousi R
    Sci Rep; 2023 Apr; 13(1):6184. PubMed ID: 37061563
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.
    Hosseini SR; Zhou X
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36562722
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores.
    El Khili MR; Memon SA; Emad A
    Bioinformatics; 2023 Apr; 39(4):. PubMed ID: 37021933
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SYNPRED: prediction of drug combination effects in cancer using different synergy metrics and ensemble learning.
    Preto AJ; Matos-Filipe P; Mourão J; Moreira IS
    Gigascience; 2022 Sep; 11():. PubMed ID: 36155782
    [TBL] [Abstract][Full Text] [Related]  

  • 20. DeepTraSynergy: drug combinations using multimodal deep learning with transformers.
    Rafiei F; Zeraati H; Abbasi K; Ghasemi JB; Parsaeian M; Masoudi-Nejad A
    Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37467066
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 13.