BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

122 related articles for article (PubMed ID: 15248526)

  • 1. The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer.
    Jaroszewicz S; Simovici DA; Kuo WP; Ohno-Machado L
    IEEE Trans Biomed Eng; 2004 Jul; 51(7):1095-102. PubMed ID: 15248526
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Induction of comprehensible models for gene expression datasets by subgroup discovery methodology.
    Gamberger D; Lavrac N; Zelezný F; Tolar J
    J Biomed Inform; 2004 Aug; 37(4):269-84. PubMed ID: 15465480
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Cancer classification and prediction using logistic regression with Bayesian gene selection.
    Zhou X; Liu KY; Wong ST
    J Biomed Inform; 2004 Aug; 37(4):249-59. PubMed ID: 15465478
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Independent component analysis-based penalized discriminant method for tumor classification using gene expression data.
    Huang DS; Zheng CH
    Bioinformatics; 2006 Aug; 22(15):1855-62. PubMed ID: 16709589
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comprehensive vertical sample-based KNN/LSVM classification for gene expression analysis.
    Pan F; Wang B; Hu X; Perrizo W
    J Biomed Inform; 2004 Aug; 37(4):240-8. PubMed ID: 15465477
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Microarray-based cancer diagnosis with artificial neural networks.
    Ringnér M; Peterson C
    Biotechniques; 2003 Mar; Suppl():30-5. PubMed ID: 12664682
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Structured polychotomous machine diagnosis of multiple cancer types using gene expression.
    Koo JY; Sohn I; Kim S; Lee JW
    Bioinformatics; 2006 Apr; 22(8):950-8. PubMed ID: 16452113
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A combination of rough-based feature selection and RBF neural network for classification using gene expression data.
    Chiang JH; Ho SH
    IEEE Trans Nanobioscience; 2008 Mar; 7(1):91-9. PubMed ID: 18334459
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.
    Cawley GC; Talbot NL
    Bioinformatics; 2006 Oct; 22(19):2348-55. PubMed ID: 16844704
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Microarray-based classification and clinical predictors: on combined classifiers and additional predictive value.
    Boulesteix AL; Porzelius C; Daumer M
    Bioinformatics; 2008 Aug; 24(15):1698-706. PubMed ID: 18544547
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Methods for multi-category cancer diagnosis from gene expression data: a comprehensive evaluation to inform decision support system development.
    Statnikov A; Aliferis CF; Tsamardinos I
    Stud Health Technol Inform; 2004; 107(Pt 2):813-7. PubMed ID: 15360925
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Small, fuzzy and interpretable gene expression based classifiers.
    Vinterbo SA; Kim EY; Ohno-Machado L
    Bioinformatics; 2005 May; 21(9):1964-70. PubMed ID: 15661797
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis.
    Statnikov A; Aliferis CF; Tsamardinos I; Hardin D; Levy S
    Bioinformatics; 2005 Mar; 21(5):631-43. PubMed ID: 15374862
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Constructing the gene regulation-level representation of microarray data for cancer classification.
    Wong HS; Wang HQ
    J Biomed Inform; 2008 Feb; 41(1):95-105. PubMed ID: 17499026
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Classification of intramural metastases and lymph node metastases of esophageal cancer from gene expression based on boosting and projective adaptive resonance theory.
    Takahashi H; Aoyagi K; Nakanishi Y; Sasaki H; Yoshida T; Honda H
    J Biosci Bioeng; 2006 Jul; 102(1):46-52. PubMed ID: 16952836
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Reliable classification of two-class cancer data using evolutionary algorithms.
    Deb K; Raji Reddy A
    Biosystems; 2003 Nov; 72(1-2):111-29. PubMed ID: 14642662
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Consensus analysis of multiple classifiers using non-repetitive variables: diagnostic application to microarray gene expression data.
    Su Z; Hong H; Perkins R; Shao X; Cai W; Tong W
    Comput Biol Chem; 2007 Feb; 31(1):48-56. PubMed ID: 17303535
    [TBL] [Abstract][Full Text] [Related]  

  • 18. PACK: Profile Analysis using Clustering and Kurtosis to find molecular classifiers in cancer.
    Teschendorff AE; Naderi A; Barbosa-Morais NL; Caldas C
    Bioinformatics; 2006 Sep; 22(18):2269-75. PubMed ID: 16682424
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Divisive Correlation Clustering Algorithm (DCCA) for grouping of genes: detecting varying patterns in expression profiles.
    Bhattacharya A; De RK
    Bioinformatics; 2008 Jun; 24(11):1359-66. PubMed ID: 18407922
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Large scale data mining approach for gene-specific standardization of microarray gene expression data.
    Yoon S; Yang Y; Choi J; Seong J
    Bioinformatics; 2006 Dec; 22(23):2898-904. PubMed ID: 17032674
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.