107 related articles for article (PubMed ID: 15706506)
1. 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]
2. Kernel Cox regression models for linking gene expression profiles to censored survival data.
Li H; Luan Y
Pac Symp Biocomput; 2003; ():65-76. PubMed ID: 12603018
[TBL] [Abstract][Full Text] [Related]
3. Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data.
Gui J; Li H
Bioinformatics; 2005 Jul; 21(13):3001-8. PubMed ID: 15814556
[TBL] [Abstract][Full Text] [Related]
4. Microarray gene expression data with linked survival phenotypes: diffuse large-B-cell lymphoma revisited.
Segal MR
Biostatistics; 2006 Apr; 7(2):268-85. PubMed ID: 16284340
[TBL] [Abstract][Full Text] [Related]
5. Boosting method for nonlinear transformation models with censored survival data.
Lu W; Li L
Biostatistics; 2008 Oct; 9(4):658-67. PubMed ID: 18344565
[TBL] [Abstract][Full Text] [Related]
6. Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes.
Lossos IS; Czerwinski DK; Alizadeh AA; Wechser MA; Tibshirani R; Botstein D; Levy R
N Engl J Med; 2004 Apr; 350(18):1828-37. PubMed ID: 15115829
[TBL] [Abstract][Full Text] [Related]
7. [Analysis of genomic copy number alterations of malignant lymphomas and its application for diagnosis].
Tagawa H
Gan To Kagaku Ryoho; 2007 Jul; 34(7):975-82. PubMed ID: 17637530
[TBL] [Abstract][Full Text] [Related]
8. Partial least squares dimension reduction for microarray gene expression data with a censored response.
Nguyen DV
Math Biosci; 2005 Jan; 193(1):119-37. PubMed ID: 15681279
[TBL] [Abstract][Full Text] [Related]
9. Prediction of recurrence-free survival in postoperative non-small cell lung cancer patients by using an integrated model of clinical information and gene expression.
Lee ES; Son DS; Kim SH; Lee J; Jo J; Han J; Kim H; Lee HJ; Choi HY; Jung Y; Park M; Lim YS; Kim K; Shim Y; Kim BC; Lee K; Huh N; Ko C; Park K; Lee JW; Choi YS; Kim J
Clin Cancer Res; 2008 Nov; 14(22):7397-404. PubMed ID: 19010856
[TBL] [Abstract][Full Text] [Related]
10. On the prognostic value of survival models with application to gene expression signatures.
Hielscher T; Zucknick M; Werft W; Benner A
Stat Med; 2010 Mar; 29(7-8):818-29. PubMed ID: 20213714
[TBL] [Abstract][Full Text] [Related]
11. Dimension reduction methods for microarrays with application to censored survival data.
Li L; Li H
Bioinformatics; 2004 Dec; 20(18):3406-12. PubMed ID: 15256406
[TBL] [Abstract][Full Text] [Related]
12. Challenges in projecting clustering results across gene expression-profiling datasets.
Lusa L; McShane LM; Reid JF; De Cecco L; Ambrogi F; Biganzoli E; Gariboldi M; Pierotti MA
J Natl Cancer Inst; 2007 Nov; 99(22):1715-23. PubMed ID: 18000217
[TBL] [Abstract][Full Text] [Related]
13. Randomized maps for assessing the reliability of patients clusters in DNA microarray data analyses.
Bertoni A; Valentini G
Artif Intell Med; 2006 Jun; 37(2):85-109. PubMed ID: 16720093
[TBL] [Abstract][Full Text] [Related]
14. Doubly penalized buckley-james method for survival data with high-dimensional covariates.
Wang S; Nan B; Zhu J; Beer DG
Biometrics; 2008 Mar; 64(1):132-40. PubMed ID: 17680828
[TBL] [Abstract][Full Text] [Related]
15. Cluster stability scores for microarray data in cancer studies.
Smolkin M; Ghosh D
BMC Bioinformatics; 2003 Sep; 4():36. PubMed ID: 12959646
[TBL] [Abstract][Full Text] [Related]
16. Partial Cox regression analysis for high-dimensional microarray gene expression data.
Li H; Gui J
Bioinformatics; 2004 Aug; 20 Suppl 1():i208-15. PubMed ID: 15262801
[TBL] [Abstract][Full Text] [Related]
17. Molecular diagnosis of lymphoma: outcome prediction by gene expression profiling in diffuse large B-cell lymphoma.
Last K; Debarnardi S; Lister TA
Methods Mol Med; 2005; 115():15-63. PubMed ID: 15998962
[TBL] [Abstract][Full Text] [Related]
18. Profiling of apoptosis genes allows for clinical stratification of primary nodal diffuse large B-cell lymphomas.
Muris JJ; Ylstra B; Cillessen SA; Ossenkoppele GJ; Kluin-Nelemans JC; Eijk PP; Nota B; Tijssen M; de Boer WP; van de Wiel M; van den Ijssel PR; Jansen P; de Bruin PC; van Krieken JH; Meijer GA; Meijer CJ; Oudejans JJ
Br J Haematol; 2007 Jan; 136(1):38-47. PubMed ID: 17062006
[TBL] [Abstract][Full Text] [Related]
19. A Laplace mixture model for identification of differential expression in microarray experiments.
Bhowmick D; Davison AC; Goldstein DR; Ruffieux Y
Biostatistics; 2006 Oct; 7(4):630-41. PubMed ID: 16565148
[TBL] [Abstract][Full Text] [Related]
20. Boosting proportional hazards models using smoothing splines, with applications to high-dimensional microarray data.
Li H; Luan Y
Bioinformatics; 2005 May; 21(10):2403-9. PubMed ID: 15713732
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
