158 related articles for article (PubMed ID: 27525863)
1. Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.
Chai H; Huang HH; Jiang HK; Liang Y; Xia LY
Genet Mol Res; 2016 Jul; 15(3):. PubMed ID: 27525863
[TBL] [Abstract][Full Text] [Related]
2. Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data.
Becker N; Toedt G; Lichter P; Benner A
BMC Bioinformatics; 2011 May; 12():138. PubMed ID: 21554689
[TBL] [Abstract][Full Text] [Related]
3. Hybrid huberized support vector machines for microarray classification and gene selection.
Wang L; Zhu J; Zou H
Bioinformatics; 2008 Feb; 24(3):412-9. PubMed ID: 18175770
[TBL] [Abstract][Full Text] [Related]
4. Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification.
Liang Y; Liu C; Luan XZ; Leung KS; Chan TM; Xu ZB; Zhang H
BMC Bioinformatics; 2013 Jun; 14():198. PubMed ID: 23777239
[TBL] [Abstract][Full Text] [Related]
5. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.
Chen Z; Li J; Wei L
Artif Intell Med; 2007 Oct; 41(2):161-75. PubMed ID: 17851055
[TBL] [Abstract][Full Text] [Related]
6. penalizedSVM: a R-package for feature selection SVM classification.
Becker N; Werft W; Toedt G; Lichter P; Benner A
Bioinformatics; 2009 Jul; 25(13):1711-2. PubMed ID: 19398451
[TBL] [Abstract][Full Text] [Related]
7. BMRF-MI: integrative identification of protein interaction network by modeling the gene dependency.
Shi X; Wang X; Shajahan A; Hilakivi-Clarke L; Clarke R; Xuan J
BMC Genomics; 2015; 16 Suppl 7(Suppl 7):S10. PubMed ID: 26099273
[TBL] [Abstract][Full Text] [Related]
8. Hybrid Framework Using Multiple-Filters and an Embedded Approach for an Efficient Selection and Classification of Microarray Data.
Bonilla-Huerta E; Hernández-Montiel A; Caporal RM; López MA
IEEE/ACM Trans Comput Biol Bioinform; 2016; 13(1):12-26. PubMed ID: 26336138
[TBL] [Abstract][Full Text] [Related]
9. Gene-expression-based cancer subtypes prediction through feature selection and transductive SVM.
Maulik U; Mukhopadhyay A; Chakraborty D
IEEE Trans Biomed Eng; 2013 Apr; 60(4):1111-7. PubMed ID: 23095982
[TBL] [Abstract][Full Text] [Related]
10. Gene and sample selection using T-score with sample selection.
Mundra PA; Rajapakse JC
J Biomed Inform; 2016 Feb; 59():31-41. PubMed ID: 26556644
[TBL] [Abstract][Full Text] [Related]
11. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine.
Xi M; Sun J; Liu L; Fan F; Wu X
Comput Math Methods Med; 2016; 2016():3572705. PubMed ID: 27642363
[TBL] [Abstract][Full Text] [Related]
12. Stable gene selection from microarray data via sample weighting.
Yu L; Han Y; Berens ME
IEEE/ACM Trans Comput Biol Bioinform; 2012; 9(1):262-72. PubMed ID: 21383420
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. A DSRPCL-SVM approach to informative gene analysis.
Xiong W; Cai Z; Ma J
Genomics Proteomics Bioinformatics; 2008 Jun; 6(2):83-90. PubMed ID: 18973864
[TBL] [Abstract][Full Text] [Related]
15. Cancer classification from gene expression data by NPPC ensemble.
Ghorai S; Mukherjee A; Sengupta S; Dutta PK
IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(3):659-71. PubMed ID: 20479504
[TBL] [Abstract][Full Text] [Related]
16. Tumor classification ranking from microarray data.
Hewett R; Kijsanayothin P
BMC Genomics; 2008 Sep; 9 Suppl 2(Suppl 2):S21. PubMed ID: 18831787
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. A balanced iterative random forest for gene selection from microarray data.
Anaissi A; Kennedy PJ; Goyal M; Catchpoole DR
BMC Bioinformatics; 2013 Aug; 14():261. PubMed ID: 23981907
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. The L(1/2) regularization approach for survival analysis in the accelerated failure time model.
Chai H; Liang Y; Liu XY
Comput Biol Med; 2015 Sep; 64():283-90. PubMed ID: 25262114
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
