135 related articles for article (PubMed ID: 16554338)
21. Bladder cancer stage and outcome by array-based comparative genomic hybridization.
Blaveri E; Brewer JL; Roydasgupta R; Fridlyand J; DeVries S; Koppie T; Pejavar S; Mehta K; Carroll P; Simko JP; Waldman FM
Clin Cancer Res; 2005 Oct; 11(19 Pt 1):7012-22. PubMed ID: 16203795
[TBL] [Abstract][Full Text] [Related]
22. Mixture classification model based on clinical markers for breast cancer prognosis.
Zeng T; Liu J
Artif Intell Med; 2010; 48(2-3):129-37. PubMed ID: 20005686
[TBL] [Abstract][Full Text] [Related]
23. Predicting the prognosis of hepatocellular carcinoma using gene expression.
Chang SH; Suh KS; Yi NJ; Lee KH; Kim BY; Jang JJ
J Surg Res; 2011 Dec; 171(2):524-31. PubMed ID: 20828739
[TBL] [Abstract][Full Text] [Related]
24. Cox survival analysis of microarray gene expression data using correlation principal component regression.
Zhao Q; Sun J
Stat Appl Genet Mol Biol; 2007; 6():Article16. PubMed ID: 17542778
[TBL] [Abstract][Full Text] [Related]
25. High expression of the transcriptional co-activator p300 predicts poor survival in resectable non-small cell lung cancers.
Hou X; Li Y; Luo RZ; Fu JH; He JH; Zhang LJ; Yang HX
Eur J Surg Oncol; 2012 Jun; 38(6):523-30. PubMed ID: 22440742
[TBL] [Abstract][Full Text] [Related]
26. Cross-platform comparison and visualisation of gene expression data using co-inertia analysis.
Culhane AC; Perrière G; Higgins DG
BMC Bioinformatics; 2003 Nov; 4():59. PubMed ID: 14633289
[TBL] [Abstract][Full Text] [Related]
27. Constructing molecular classifiers for the accurate prognosis of lung adenocarcinoma.
Guo L; Ma Y; Ward R; Castranova V; Shi X; Qian Y
Clin Cancer Res; 2006 Jun; 12(11 Pt 1):3344-54. PubMed ID: 16740756
[TBL] [Abstract][Full Text] [Related]
28. Kernel mixture survival models for identifying cancer subtypes, predicting patient's cancer types and survival probabilities.
Ando T; Imoto S; Miyano S
Genome Inform; 2004; 15(2):201-10. PubMed ID: 15706506
[TBL] [Abstract][Full Text] [Related]
29. An empirical Bayesian method for estimating biological networks from temporal microarray data.
Rau A; Jaffrézic F; Foulley JL; Doerge RW
Stat Appl Genet Mol Biol; 2010; 9():Article 9. PubMed ID: 20196759
[TBL] [Abstract][Full Text] [Related]
30. Multiple gene expression classifiers from different array platforms predict poor prognosis of colorectal cancer.
Lin YH; Friederichs J; Black MA; Mages J; Rosenberg R; Guilford PJ; Phillips V; Thompson-Fawcett M; Kasabov N; Toro T; Merrie AE; van Rij A; Yoon HS; McCall JL; Siewert JR; Holzmann B; Reeve AE
Clin Cancer Res; 2007 Jan; 13(2 Pt 1):498-507. PubMed ID: 17255271
[TBL] [Abstract][Full Text] [Related]
31. Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.
Cawley GC; Talbot NL
Bioinformatics; 2006 Oct; 22(19):2348-55. PubMed ID: 16844704
[TBL] [Abstract][Full Text] [Related]
32. RANTES expression is a predictor of survival in stage I lung adenocarcinoma.
Moran CJ; Arenberg DA; Huang CC; Giordano TJ; Thomas DG; Misek DE; Chen G; Iannettoni MD; Orringer MB; Hanash S; Beer DG
Clin Cancer Res; 2002 Dec; 8(12):3803-12. PubMed ID: 12473593
[TBL] [Abstract][Full Text] [Related]
33. Increased expression of the LGALS3 (galectin 3) gene in human non-small-cell lung cancer.
Yoshimura A; Gemma A; Hosoya Y; Komaki E; Hosomi Y; Okano T; Takenaka K; Matuda K; Seike M; Uematsu K; Hibino S; Shibuya M; Yamada T; Hirohashi S; Kudoh S
Genes Chromosomes Cancer; 2003 Jun; 37(2):159-64. PubMed ID: 12696064
[TBL] [Abstract][Full Text] [Related]
34. Prediction of lymph node metastasis by gene expression profiling in patients with primary resected lung cancer.
Moriya Y; Iyoda A; Kasai Y; Sugimoto T; Hashida J; Nimura Y; Kato M; Takiguchi M; Fujisawa T; Seki N; Yoshino I
Lung Cancer; 2009 Apr; 64(1):86-91. PubMed ID: 18930562
[TBL] [Abstract][Full Text] [Related]
35. Bayesian profiling of molecular signatures to predict event times.
Zhang D; Zhang M
Theor Biol Med Model; 2007 Jan; 4():3. PubMed ID: 17239251
[TBL] [Abstract][Full Text] [Related]
36. Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.
Xu H; Moni MA; Liò P
Comput Biol Chem; 2015 Dec; 59 Pt B():15-31. PubMed ID: 26611766
[TBL] [Abstract][Full Text] [Related]
37. Pathway-Structured Predictive Model for Cancer Survival Prediction: A Two-Stage Approach.
Zhang X; Li Y; Akinyemiju T; Ojesina AI; Buckhaults P; Liu N; Xu B; Yi N
Genetics; 2017 Jan; 205(1):89-100. PubMed ID: 28049703
[TBL] [Abstract][Full Text] [Related]
38. Risk classification of cancer survival using ANN with gene expression data from multiple laboratories.
Chen YC; Ke WC; Chiu HW
Comput Biol Med; 2014 May; 48():1-7. PubMed ID: 24631783
[TBL] [Abstract][Full Text] [Related]
39. Analysis of the microarray gene expression for breast cancer progression after the application modified logistic regression.
Morais-Rodrigues F; Silv Erio-Machado R; Kato RB; Rodrigues DLN; Valdez-Baez J; Fonseca V; San EJ; Gomes LGR; Dos Santos RG; Vinicius Canário Viana M; da Cruz Ferraz Dutra J; Teixeira Dornelles Parise M; Parise D; Campos FF; de Souza SJ; Ortega JM; Barh D; Ghosh P; Azevedo VAC; Dos Santos MA
Gene; 2020 Feb; 726():144168. PubMed ID: 31759986
[TBL] [Abstract][Full Text] [Related]
40. Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.
Liang Y; Chai H; Liu XY; Xu ZB; Zhang H; Leung KS
BMC Med Genomics; 2016 Mar; 9():11. PubMed ID: 26932592
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
