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.
202 related articles for article (PubMed ID: 15598834)
1. LS Bound based gene selection for DNA microarray data. Zhou X; Mao KZ Bioinformatics; 2005 Apr; 21(8):1559-64. PubMed ID: 15598834 [TBL] [Abstract][Full Text] [Related]
2. The ties problem resulting from counting-based error estimators and its impact on gene selection algorithms. Zhou X; Mao KZ Bioinformatics; 2006 Oct; 22(20):2507-15. PubMed ID: 16908500 [TBL] [Abstract][Full Text] [Related]
3. 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]
4. Development of two-stage SVM-RFE gene selection strategy for microarray expression data analysis. Tang Y; Zhang YQ; Huang Z IEEE/ACM Trans Comput Biol Bioinform; 2007; 4(3):365-81. PubMed ID: 17666757 [TBL] [Abstract][Full Text] [Related]
5. Gene selection algorithms for microarray data based on least squares support vector machine. Tang EK; Suganthan PN; Yao X BMC Bioinformatics; 2006 Feb; 7():95. PubMed ID: 16504159 [TBL] [Abstract][Full Text] [Related]
6. Analysis of recursive gene selection approaches from microarray data. Li F; Yang Y Bioinformatics; 2005 Oct; 21(19):3741-7. PubMed ID: 16118263 [TBL] [Abstract][Full Text] [Related]
8. Regularized Least Squares Cancer classifiers from DNA microarray data. Ancona N; Maglietta R; D'Addabbo A; Liuni S; Pesole G BMC Bioinformatics; 2005 Dec; 6 Suppl 4(Suppl 4):S2. PubMed ID: 16351746 [TBL] [Abstract][Full Text] [Related]
9. Discovery of highly differentiative gene groups from microarray gene expression data using the gene club approach. Mao S; Dong G J Bioinform Comput Biol; 2005 Dec; 3(6):1263-80. PubMed ID: 16374906 [TBL] [Abstract][Full Text] [Related]
10. Eigengene-based linear discriminant model for tumor classification using gene expression microarray data. Shen R; Ghosh D; Chinnaiyan A; Meng Z Bioinformatics; 2006 Nov; 22(21):2635-42. PubMed ID: 16926220 [TBL] [Abstract][Full Text] [Related]
11. 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]
12. Regularization network-based gene selection for microarray data analysis. Zhou X; Mao KZ Int J Neural Syst; 2006 Oct; 16(5):341-52. PubMed ID: 17117495 [TBL] [Abstract][Full Text] [Related]
13. Bayesian model averaging: development of an improved multi-class, gene selection and classification tool for microarray data. Yeung KY; Bumgarner RE; Raftery AE Bioinformatics; 2005 May; 21(10):2394-402. PubMed ID: 15713736 [TBL] [Abstract][Full Text] [Related]
14. Classification using partial least squares with penalized logistic regression. Fort G; Lambert-Lacroix S Bioinformatics; 2005 Apr; 21(7):1104-11. PubMed ID: 15531609 [TBL] [Abstract][Full Text] [Related]
15. Wrapper-based gene selection with Markov blanket. Wang A; An N; Yang J; Chen G; Li L; Alterovitz G Comput Biol Med; 2017 Feb; 81():11-23. PubMed ID: 28006702 [TBL] [Abstract][Full Text] [Related]
16. Selecting dissimilar genes for multi-class classification, an application in cancer subtyping. Cai Z; Goebel R; Salavatipour MR; Lin G BMC Bioinformatics; 2007 Jun; 8():206. PubMed ID: 17573973 [TBL] [Abstract][Full Text] [Related]
17. Multiple SVM-RFE for gene selection in cancer classification with expression data. Duan KB; Rajapakse JC; Wang H; Azuaje F IEEE Trans Nanobioscience; 2005 Sep; 4(3):228-34. PubMed ID: 16220686 [TBL] [Abstract][Full Text] [Related]
18. Multi-class cancer classification via partial least squares with gene expression profiles. Nguyen DV; Rocke DM Bioinformatics; 2002 Sep; 18(9):1216-26. PubMed ID: 12217913 [TBL] [Abstract][Full Text] [Related]
19. Recursive Mahalanobis separability measure for gene subset selection. Mao KZ; Tang W IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(1):266-72. PubMed ID: 20479500 [TBL] [Abstract][Full Text] [Related]
20. An efficient semi-unsupervised gene selection method via spectral biclustering. Liu B; Wan C; Wang L IEEE Trans Nanobioscience; 2006 Jun; 5(2):110-4. PubMed ID: 16805107 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]