172 related articles for article (PubMed ID: 26647162)
1. iRDA: a new filter towards predictive, stable, and enriched candidate genes.
Lai HM; Albrecht AA; Steinhöfel KK
BMC Genomics; 2015 Dec; 16():1041. PubMed ID: 26647162
[TBL] [Abstract][Full Text] [Related]
2. BubbleGUM: automatic extraction of phenotype molecular signatures and comprehensive visualization of multiple Gene Set Enrichment Analyses.
Spinelli L; Carpentier S; Montañana Sanchis F; Dalod M; Vu Manh TP
BMC Genomics; 2015 Oct; 16():814. PubMed ID: 26481321
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Feature selection and nearest centroid classification for protein mass spectrometry.
Levner I
BMC Bioinformatics; 2005 Mar; 6():68. PubMed ID: 15788095
[TBL] [Abstract][Full Text] [Related]
5. Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery.
Grate LR
BMC Bioinformatics; 2005 Apr; 6():97. PubMed ID: 15826317
[TBL] [Abstract][Full Text] [Related]
6. An experimental comparison of feature selection methods on two-class biomedical datasets.
Drotár P; Gazda J; Smékal Z
Comput Biol Med; 2015 Nov; 66():1-10. PubMed ID: 26327447
[TBL] [Abstract][Full Text] [Related]
7. Gene expression analysis in clear cell renal cell carcinoma using gene set enrichment analysis for biostatistical management.
Maruschke M; Reuter D; Koczan D; Hakenberg OW; Thiesen HJ
BJU Int; 2011 Jul; 108(2 Pt 2):E29-35. PubMed ID: 21435154
[TBL] [Abstract][Full Text] [Related]
8. Comparative study of gene set enrichment methods.
Abatangelo L; Maglietta R; Distaso A; D'Addabbo A; Creanza TM; Mukherjee S; Ancona N
BMC Bioinformatics; 2009 Sep; 10():275. PubMed ID: 19725948
[TBL] [Abstract][Full Text] [Related]
9. A survey on filter techniques for feature selection in gene expression microarray analysis.
Lazar C; Taminau J; Meganck S; Steenhoff D; Coletta A; Molter C; de Schaetzen V; Duque R; Bersini H; Nowé A
IEEE/ACM Trans Comput Biol Bioinform; 2012; 9(4):1106-19. PubMed ID: 22350210
[TBL] [Abstract][Full Text] [Related]
10. A novel feature selection approach for biomedical data classification.
Peng Y; Wu Z; Jiang J
J Biomed Inform; 2010 Feb; 43(1):15-23. PubMed ID: 19647098
[TBL] [Abstract][Full Text] [Related]
11. Identification of potential biomarkers on microarray data using distributed gene selection approach.
Shukla AK; Tripathi D
Math Biosci; 2019 Sep; 315():108230. PubMed ID: 31326384
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Peculiar Genes Selection: A new features selection method to improve classification performances in imbalanced data sets.
Martina F; Beccuti M; Balbo G; Cordero F
PLoS One; 2017; 12(8):e0177475. PubMed ID: 28806759
[TBL] [Abstract][Full Text] [Related]
14. Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.
Lai Y; Zhang F; Nayak TK; Modarres R; Lee NH; McCaffrey TA
BMC Genomics; 2017 Jan; 18(Suppl 1):1050. PubMed ID: 28198679
[TBL] [Abstract][Full Text] [Related]
15. Filter versus wrapper gene selection approaches in DNA microarray domains.
Inza I; Larrañaga P; Blanco R; Cerrolaza AJ
Artif Intell Med; 2004 Jun; 31(2):91-103. PubMed ID: 15219288
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.
Sun L; Wang J; Wei J
BMC Bioinformatics; 2017 Mar; 18(Suppl 3):50. PubMed ID: 28361689
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Exploring correlations in gene expression microarray data for maximum predictive-minimum redundancy biomarker selection and classification.
Arevalillo JM; Navarro H
Comput Biol Med; 2013 Oct; 43(10):1437-43. PubMed ID: 24034735
[TBL] [Abstract][Full Text] [Related]
20. Ensemble gene selection by grouping for microarray data classification.
Liu H; Liu L; Zhang H
J Biomed Inform; 2010 Feb; 43(1):81-7. PubMed ID: 19699316
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]