230 related articles for article (PubMed ID: 22889876)
21. Random forests on distance matrices for imaging genetics studies.
Sim A; Tsagkrasoulis D; Montana G
Stat Appl Genet Mol Biol; 2013 Dec; 12(6):757-86. PubMed ID: 24246292
[TBL] [Abstract][Full Text] [Related]
22. A multicenter random forest model for effective prognosis prediction in collaborative clinical research network.
Li J; Tian Y; Zhu Y; Zhou T; Li J; Ding K; Li J
Artif Intell Med; 2020 Mar; 103():101814. PubMed ID: 32143809
[TBL] [Abstract][Full Text] [Related]
23. Random forests for genomic data analysis.
Chen X; Ishwaran H
Genomics; 2012 Jun; 99(6):323-9. PubMed ID: 22546560
[TBL] [Abstract][Full Text] [Related]
24. An experimental bias-variance analysis of SVM ensembles based on resampling techniques.
Valentini G
IEEE Trans Syst Man Cybern B Cybern; 2005 Dec; 35(6):1252-71. PubMed ID: 16366250
[TBL] [Abstract][Full Text] [Related]
25. Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers.
Barenboim M; Masso M; Vaisman II; Jamison DC
Proteins; 2008 Jun; 71(4):1930-9. PubMed ID: 18186470
[TBL] [Abstract][Full Text] [Related]
26. SNP interaction detection with Random Forests in high-dimensional genetic data.
Winham SJ; Colby CL; Freimuth RR; Wang X; de Andrade M; Huebner M; Biernacka JM
BMC Bioinformatics; 2012 Jul; 13():164. PubMed ID: 22793366
[TBL] [Abstract][Full Text] [Related]
27. Performance of random forest when SNPs are in linkage disequilibrium.
Meng YA; Yu Y; Cupples LA; Farrer LA; Lunetta KL
BMC Bioinformatics; 2009 Mar; 10():78. PubMed ID: 19265542
[TBL] [Abstract][Full Text] [Related]
28. Bootstrap aggregating of alternating decision trees to detect sets of SNPs that associate with disease.
Guy RT; Santago P; Langefeld CD
Genet Epidemiol; 2012 Feb; 36(2):99-106. PubMed ID: 22851473
[TBL] [Abstract][Full Text] [Related]
29. Avoiding the high Bonferroni penalty in genome-wide association studies.
Gao X; Becker LC; Becker DM; Starmer JD; Province MA
Genet Epidemiol; 2010 Jan; 34(1):100-5. PubMed ID: 19434714
[TBL] [Abstract][Full Text] [Related]
30. Random forests for classification in ecology.
Cutler DR; Edwards TC; Beard KH; Cutler A; Hess KT; Gibson J; Lawler JJ
Ecology; 2007 Nov; 88(11):2783-92. PubMed ID: 18051647
[TBL] [Abstract][Full Text] [Related]
31. SNP selection and classification of genome-wide SNP data using stratified sampling random forests.
Wu Q; Ye Y; Liu Y; Ng MK
IEEE Trans Nanobioscience; 2012 Sep; 11(3):216-27. PubMed ID: 22987127
[TBL] [Abstract][Full Text] [Related]
32. fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies.
Lin J; Sibley A; Shterev I; Nixon A; Innocenti F; Chan C; Owzar K
BMC Bioinformatics; 2019 Jun; 20(1):333. PubMed ID: 31195980
[TBL] [Abstract][Full Text] [Related]
33. Strengths, Weaknesses, Opportunities, and Threats Analysis of Artificial Intelligence and Machine Learning Applications in Radiology.
Martín Noguerol T; Paulano-Godino F; Martín-Valdivia MT; Menias CO; Luna A
J Am Coll Radiol; 2019 Sep; 16(9 Pt B):1239-1247. PubMed ID: 31492401
[TBL] [Abstract][Full Text] [Related]
34. Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction.
López B; Torrent-Fontbona F; Viñas R; Fernández-Real JM
Artif Intell Med; 2018 Apr; 85():43-49. PubMed ID: 28943335
[TBL] [Abstract][Full Text] [Related]
35. Application of two machine learning algorithms to genetic association studies in the presence of covariates.
Nonyane BA; Foulkes AS
BMC Genet; 2008 Nov; 9():71. PubMed ID: 19014573
[TBL] [Abstract][Full Text] [Related]
36. The behaviour of random forest permutation-based variable importance measures under predictor correlation.
Nicodemus KK; Malley JD; Strobl C; Ziegler A
BMC Bioinformatics; 2010 Feb; 11():110. PubMed ID: 20187966
[TBL] [Abstract][Full Text] [Related]
37. Integrated analysis of pharmacologic, clinical and SNP microarray data using Projection Onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing.
Pounds S; Cao X; Cheng C; Yang JJ; Campana D; Pui CH; Evans WE; Relling MV
Int J Data Min Bioinform; 2011; 5(2):143-57. PubMed ID: 21516175
[TBL] [Abstract][Full Text] [Related]
38. Hybrid of Restricted and Penalized Maximum Likelihood Method for Efficient Genome-Wide Association Study.
Ren W; Liang Z; He S; Xiao J
Genes (Basel); 2020 Oct; 11(11):. PubMed ID: 33138126
[TBL] [Abstract][Full Text] [Related]
39. SHARE: an adaptive algorithm to select the most informative set of SNPs for candidate genetic association.
Dai JY; Leblanc M; Smith NL; Psaty B; Kooperberg C
Biostatistics; 2009 Oct; 10(4):680-93. PubMed ID: 19605740
[TBL] [Abstract][Full Text] [Related]
40. Genome-wide prediction using Bayesian additive regression trees.
Waldmann P
Genet Sel Evol; 2016 Jun; 48(1):42. PubMed ID: 27286957
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]