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 *

137 related articles for article (PubMed ID: 27481519)

  • 1. SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.
    Shahid M; Shahzad Cheema M; Klenner A; Younesi E; Hofmann-Apitius M
    Mol Inform; 2013 Mar; 32(3):241-9. PubMed ID: 27481519
    [TBL] [Abstract][Full Text] [Related]  

  • 2. In silico prediction of major drug clearance pathways by support vector machines with feature-selected descriptors.
    Toshimoto K; Wakayama N; Kusama M; Maeda K; Sugiyama Y; Akiyama Y
    Drug Metab Dispos; 2014 Nov; 42(11):1811-9. PubMed ID: 25128502
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE.
    Niijima S; Kuhara S
    BMC Bioinformatics; 2006 Dec; 7():543. PubMed ID: 17187691
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Effect of molecular descriptor feature selection in support vector machine classification of pharmacokinetic and toxicological properties of chemical agents.
    Xue Y; Li ZR; Yap CW; Sun LZ; Chen X; Chen YZ
    J Chem Inf Comput Sci; 2004; 44(5):1630-8. PubMed ID: 15446820
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SVM-RFE: selection and visualization of the most relevant features through non-linear kernels.
    Sanz H; Valim C; Vegas E; Oller JM; Reverter F
    BMC Bioinformatics; 2018 Nov; 19(1):432. PubMed ID: 30453885
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Drug/nondrug classification using Support Vector Machines with various feature selection strategies.
    Korkmaz S; Zararsiz G; Goksuluk D
    Comput Methods Programs Biomed; 2014 Nov; 117(2):51-60. PubMed ID: 25224081
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Tuning to optimize SVM approach for assisting ovarian cancer diagnosis with photoacoustic imaging.
    Wang R; Li R; Lei Y; Zhu Q
    Biomed Mater Eng; 2015; 26 Suppl 1():S975-81. PubMed ID: 26406101
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of chemical carcinogenicity by machine learning approaches.
    Tan NX; Rao HB; Li ZR; Li XY
    SAR QSAR Environ Res; 2009; 20(1-2):27-75. PubMed ID: 19343583
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics.
    Lin X; Li C; Zhang Y; Su B; Fan M; Wei H
    Molecules; 2017 Dec; 23(1):. PubMed ID: 29278382
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A support vector machine-recursive feature elimination feature selection method based on artificial contrast variables and mutual information.
    Lin X; Yang F; Zhou L; Yin P; Kong H; Xing W; Lu X; Jia L; Wang Q; Xu G
    J Chromatogr B Analyt Technol Biomed Life Sci; 2012 Dec; 910():149-55. PubMed ID: 22682888
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.
    Sahran S; Albashish D; Abdullah A; Shukor NA; Hayati Md Pauzi S
    Artif Intell Med; 2018 May; 87():78-90. PubMed ID: 29680688
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Enzyme classification using multiclass support vector machine and feature subset selection.
    Pradhan D; Padhy S; Sahoo B
    Comput Biol Chem; 2017 Oct; 70():211-219. PubMed ID: 28934693
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Recursive Support Vector Machine Biomarker Selection for Alzheimer's Disease.
    Zhang F; Petersen M; Johnson L; Hall J; O'Bryant SE
    J Alzheimers Dis; 2021; 79(4):1691-1700. PubMed ID: 33492292
    [TBL] [Abstract][Full Text] [Related]  

  • 14. MSVM-RFE: extensions of SVM-RFE for multiclass gene selection on DNA microarray data.
    Zhou X; Tuck DP
    Bioinformatics; 2007 May; 23(9):1106-14. PubMed ID: 17494773
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A comprehensive support vector machine binary hERG classification model based on extensive but biased end point hERG data sets.
    Shen MY; Su BH; Esposito EX; Hopfinger AJ; Tseng YJ
    Chem Res Toxicol; 2011 Jun; 24(6):934-49. PubMed ID: 21504223
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Improving the computational efficiency of recursive cluster elimination for gene selection.
    Luo LK; Huang DF; Ye LJ; Zhou QF; Shao GF; Peng H
    IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(1):122-9. PubMed ID: 20479497
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Classification study of skin sensitizers based on support vector machine and linear discriminant analysis.
    Ren Y; Liu H; Xue C; Yao X; Liu M; Fan B
    Anal Chim Acta; 2006 Jul; 572(2):272-82. PubMed ID: 17723489
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of novel and selective TNF-alpha converting enzyme (TACE) inhibitors and characterization of correlative molecular descriptors by machine learning approaches.
    Cong Y; Yang XG; Lv W; Xue Y
    J Mol Graph Model; 2009 Oct; 28(3):236-44. PubMed ID: 19729328
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Recursive cluster elimination (RCE) for classification and feature selection from gene expression data.
    Yousef M; Jung S; Showe LC; Showe MK
    BMC Bioinformatics; 2007 May; 8():144. PubMed ID: 17474999
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Using classification structure pharmacokinetic relationship (SCPR) method to predict drug bioavailability based on grid-search support vector machine.
    Wang J; Du H; Yao X; Hu Z
    Anal Chim Acta; 2007 Oct; 601(2):156-63. PubMed ID: 17920387
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.