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.
157 related articles for article (PubMed ID: 25712072)
1. New feature selection for gene expression classification based on degree of class overlap in principal dimensions. Rakkeitwinai S; Lursinsap C; Aporntewan C; Mutirangura A Comput Biol Med; 2015 Sep; 64():292-8. PubMed ID: 25712072 [TBL] [Abstract][Full Text] [Related]
2. An efficient statistical feature selection approach for classification of gene expression data. Chandra B; Gupta M J Biomed Inform; 2011 Aug; 44(4):529-35. PubMed ID: 21241823 [TBL] [Abstract][Full Text] [Related]
3. Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis. Li GZ; Bu HL; Yang MQ; Zeng XQ; Yang JY BMC Genomics; 2008 Sep; 9 Suppl 2(Suppl 2):S24. PubMed ID: 18831790 [TBL] [Abstract][Full Text] [Related]
4. The feature selection bias problem in relation to high-dimensional gene data. Krawczuk J; Ćukaszuk T Artif Intell Med; 2016 Jan; 66():63-71. PubMed ID: 26674595 [TBL] [Abstract][Full Text] [Related]
5. Robust feature selection for microarray data based on multicriterion fusion. Yang F; Mao KZ IEEE/ACM Trans Comput Biol Bioinform; 2011; 8(4):1080-92. PubMed ID: 21566255 [TBL] [Abstract][Full Text] [Related]
6. Sparse maximum margin discriminant analysis for feature extraction and gene selection on gene expression data. Cui Y; Zheng CH; Yang J; Sha W Comput Biol Med; 2013 Aug; 43(7):933-41. PubMed ID: 23746736 [TBL] [Abstract][Full Text] [Related]
7. 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]
12. A fast gene selection method for multi-cancer classification using multiple support vector data description. Cao J; Zhang L; Wang B; Li F; Yang J J Biomed Inform; 2015 Feb; 53():381-9. PubMed ID: 25549938 [TBL] [Abstract][Full Text] [Related]
13. Feature weight estimation for gene selection: a local hyperlinear learning approach. Cai H; Ruan P; Ng M; Akutsu T BMC Bioinformatics; 2014 Mar; 15():70. PubMed ID: 24625071 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Nonnegative least-squares methods for the classification of high-dimensional biological data. Li Y; Ngom A IEEE/ACM Trans Comput Biol Bioinform; 2013; 10(2):447-56. PubMed ID: 23929868 [TBL] [Abstract][Full Text] [Related]
16. A granular computing approach to gene selection. Sun L; Xu J Biomed Mater Eng; 2014; 24(1):1307-14. PubMed ID: 24212026 [TBL] [Abstract][Full Text] [Related]
17. A novel gene selection algorithm for cancer classification using microarray datasets. Alanni R; Hou J; Azzawi H; Xiang Y BMC Med Genomics; 2019 Jan; 12(1):10. PubMed ID: 30646919 [TBL] [Abstract][Full Text] [Related]
18. Nonlinear dimensionality reduction of gene expression data for visualization and clustering analysis of cancer tissue samples. Shi J; Luo Z Comput Biol Med; 2010 Aug; 40(8):723-32. PubMed ID: 20637456 [TBL] [Abstract][Full Text] [Related]
19. 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]
20. Robust and stable feature selection by integrating ranking methods and wrapper technique in genetic data classification. Yassi M; Moattar MH Biochem Biophys Res Commun; 2014 Apr; 446(4):850-6. PubMed ID: 24657268 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]