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 *

144 related articles for article (PubMed ID: 18690988)

  • 1. Advances in machine learning prediction of toxicological properties and adverse drug reactions of pharmaceutical agents.
    Ma XH; Wang R; Xue Y; Li ZR; Yang SY; Wei YQ; Chen YZ
    Curr Drug Saf; 2008 May; 3(2):100-14. PubMed ID: 18690988
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.
    Ma XH; Jia J; Zhu F; Xue Y; Li ZR; Chen YZ
    Comb Chem High Throughput Screen; 2009 May; 12(4):344-57. PubMed ID: 19442064
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins.
    Li H; Yap CW; Ung CY; Xue Y; Li ZR; Han LY; Lin HH; Chen YZ
    J Pharm Sci; 2007 Nov; 96(11):2838-60. PubMed ID: 17786989
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods.
    Yap CW; Xue Y; Li H; Li ZR; Ung CY; Han LY; Zheng CJ; Cao ZW; Chen YZ
    Mini Rev Med Chem; 2006 Apr; 6(4):449-59. PubMed ID: 16613581
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine learning-based prediction of drug-drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties.
    Cheng F; Zhao Z
    J Am Med Inform Assoc; 2014 Oct; 21(e2):e278-86. PubMed ID: 24644270
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of adverse drug reactions using decision tree modeling.
    Hammann F; Gutmann H; Vogt N; Helma C; Drewe J
    Clin Pharmacol Ther; 2010 Jul; 88(1):52-9. PubMed ID: 20220749
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Use of machine learning approaches for novel drug discovery.
    Lima AN; Philot EA; Trossini GH; Scott LP; Maltarollo VG; Honorio KM
    Expert Opin Drug Discov; 2016; 11(3):225-39. PubMed ID: 26814169
    [TBL] [Abstract][Full Text] [Related]  

  • 8. In silico machine learning methods in drug development.
    Dobchev DA; Pillai GG; Karelson M
    Curr Top Med Chem; 2014; 14(16):1913-22. PubMed ID: 25262800
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Recent progresses in the application of machine learning approach for predicting protein functional class independent of sequence similarity.
    Han L; Cui J; Lin H; Ji Z; Cao Z; Li Y; Chen Y
    Proteomics; 2006 Jul; 6(14):4023-37. PubMed ID: 16791826
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine-learning approaches in drug discovery: methods and applications.
    Lavecchia A
    Drug Discov Today; 2015 Mar; 20(3):318-31. PubMed ID: 25448759
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine learning models for lipophilicity and their domain of applicability.
    Schroeter T; Schwaighofer A; Mika S; Laak AT; Suelzle D; Ganzer U; Heinrich N; Müller KR
    Mol Pharm; 2007; 4(4):524-38. PubMed ID: 17637064
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Weka machine learning for predicting the phospholipidosis inducing potential.
    Ivanciuc O
    Curr Top Med Chem; 2008; 8(18):1691-709. PubMed ID: 19075775
    [TBL] [Abstract][Full Text] [Related]  

  • 13. In silico prediction of Tetrahymena pyriformis toxicity for diverse industrial chemicals with substructure pattern recognition and machine learning methods.
    Cheng F; Shen J; Yu Y; Li W; Liu G; Lee PW; Tang Y
    Chemosphere; 2011 Mar; 82(11):1636-43. PubMed ID: 21145574
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.
    Liu M; Wu Y; Chen Y; Sun J; Zhao Z; Chen XW; Matheny ME; Xu H
    J Am Med Inform Assoc; 2012 Jun; 19(e1):e28-35. PubMed ID: 22718037
    [TBL] [Abstract][Full Text] [Related]  

  • 15. In silico ADMET prediction: recent advances, current challenges and future trends.
    Cheng F; Li W; Liu G; Tang Y
    Curr Top Med Chem; 2013; 13(11):1273-89. PubMed ID: 23675935
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tools.
    Tao L; Zhang P; Qin C; Chen SY; Zhang C; Chen Z; Zhu F; Yang SY; Wei YQ; Chen YZ
    Adv Drug Deliv Rev; 2015 Jun; 86():83-100. PubMed ID: 26037068
    [TBL] [Abstract][Full Text] [Related]  

  • 17. In Silico Prediction of Chemical-Induced Hepatocellular Hypertrophy Using Molecular Descriptors.
    Ambe K; Ishihara K; Ochibe T; Ohya K; Tamura S; Inoue K; Yoshida M; Tohkin M
    Toxicol Sci; 2018 Apr; 162(2):667-675. PubMed ID: 29309657
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning.
    Liu M; Cai R; Hu Y; Matheny ME; Sun J; Hu J; Xu H
    J Am Med Inform Assoc; 2014; 21(2):245-51. PubMed ID: 24334612
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An overview of data mining algorithms in drug induced toxicity prediction.
    Omer A; Singh P; Yadav NK; Singh RK
    Mini Rev Med Chem; 2014 Apr; 14(4):345-54. PubMed ID: 24552264
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A review on machine learning methods for in silico toxicity prediction.
    Idakwo G; Luttrell J; Chen M; Hong H; Zhou Z; Gong P; Zhang C
    J Environ Sci Health C Environ Carcinog Ecotoxicol Rev; 2018; 36(4):169-191. PubMed ID: 30628866
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.