Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 86

1.

Methods and challenges in timing chromosomal abnormalities within cancer samples.

Purdom E, Ho C, Grasso CS, Quist MJ, Cho RJ, Spellman P.

Bioinformatics. 2013 Dec 15;29(24):3113-20. doi: 10.1093/bioinformatics/btt546. Epub 2013 Sep 23.

2.

Chromosome abnormalities in ovarian adenocarcinoma: III. Using breakpoint data to infer and test mathematical models for oncogenesis.

Simon R, Desper R, Papadimitriou CH, Peng A, Alberts DS, Taetle R, Trent JM, Schäffer AA.

Genes Chromosomes Cancer. 2000 May;28(1):106-20.

PMID:
10738309
3.

MLEP: an R package for exploring the maximum likelihood estimates of penetrance parameters.

Sugaya Y.

BMC Res Notes. 2012 Aug 28;5:465. doi: 10.1186/1756-0500-5-465.

4.

A fast Bayesian change point analysis for the segmentation of microarray data.

Erdman C, Emerson JW.

Bioinformatics. 2008 Oct 1;24(19):2143-8. doi: 10.1093/bioinformatics/btn404. Epub 2008 Jul 29.

PMID:
18667443
5.

Comparative cytogenetic studies of benign, borderline, and malignant epithelial ovarian tumors.

Izutsu T, Kudo T, Shoji T, Nishiya I.

J Obstet Gynaecol Res. 1996 Dec;22(6):541-9.

PMID:
9037943
6.

High-resolution single nucleotide polymorphism array analysis of epithelial ovarian cancer reveals numerous microdeletions and amplifications.

Gorringe KL, Jacobs S, Thompson ER, Sridhar A, Qiu W, Choong DY, Campbell IG.

Clin Cancer Res. 2007 Aug 15;13(16):4731-9.

7.

[Importance of chromosomal changes correlated to prognostic factors in ovarian and cervical malignant tumors].

Jancárková N, Krkavcová M, Janashia M, Freitag P, Dusková J, Cibula D.

Ceska Gynekol. 2008 Apr;73(2):79-86. Czech.

PMID:
18567425
8.

Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data.

Ferragina A, de los Campos G, Vazquez AI, Cecchinato A, Bittante G.

J Dairy Sci. 2015 Nov;98(11):8133-51. doi: 10.3168/jds.2014-9143. Epub 2015 Sep 18.

9.

Chromosomal losses of regions on 5q and lack of high-level amplifications at 8q24 are associated with favorable prognosis for ovarian serous carcinoma.

Staebler A, Karberg B, Behm J, Kuhlmann P, Neubert U, Schmidt H, Korsching E, Bürger H, Lelle R, Kiesel L, Böcker W, Shih IeM, Buchweitz O.

Genes Chromosomes Cancer. 2006 Oct;45(10):905-17.

PMID:
16845658
10.

Empirical Bayes Gaussian likelihood estimation of exposure distributions from pooled samples in human biomonitoring.

Li X, Kuk AY, Xu J.

Stat Med. 2014 Dec 10;33(28):4999-5014. doi: 10.1002/sim.6304. Epub 2014 Sep 12.

PMID:
25213192
11.

A Bayesian group sparse multi-task regression model for imaging genetics.

Greenlaw K, Szefer E, Graham J, Lesperance M, Nathoo FS; Alzheimer’s Disease Neuroimaging Initiative.

Bioinformatics. 2017 Aug 15;33(16):2513-2522. doi: 10.1093/bioinformatics/btx215.

12.

Efficient sampling for Bayesian inference of conjunctive Bayesian networks.

Sakoparnig T, Beerenwinkel N.

Bioinformatics. 2012 Sep 15;28(18):2318-24. doi: 10.1093/bioinformatics/bts433. Epub 2012 Jul 10.

13.

Bayesian estimates of linkage disequilibrium.

Sebastiani P, Abad-Grau MM.

BMC Genet. 2007 Jun 25;8:36.

14.

Simple structural chromosomal abnormalities in advanced stage of ovarian cancer.

Panani AD, Aravidis C, Kosmaidou Z, Rodolakis A, Antsaklis A.

In Vivo. 2009 May-Jun;23(3):425-8.

15.

Pathways of urothelial cancer progression suggested by Bayesian network analysis of allelotyping data.

Bulashevska S, Szakacs O, Brors B, Eils R, Kovacs G.

Int J Cancer. 2004 Jul 20;110(6):850-6.

16.
17.

BADGE: a novel Bayesian model for accurate abundance quantification and differential analysis of RNA-Seq data.

Gu J, Wang X, Halakivi-Clarke L, Clarke R, Xuan J.

BMC Bioinformatics. 2014;15 Suppl 9:S6. doi: 10.1186/1471-2105-15-S9-S6. Epub 2014 Sep 10.

18.

Chromosomal abnormalities: detection and implications for cancer development.

Dos Santos NR, Van Kessel AG.

Anticancer Res. 1999 Nov-Dec;19(6A):4697-714. Review.

PMID:
10697586
19.

Information criteria for Firth's penalized partial likelihood approach in Cox regression models.

Nagashima K, Sato Y.

Stat Med. 2017 Sep 20;36(21):3422-3436. doi: 10.1002/sim.7368. Epub 2017 Jun 12.

20.

Empirical Bayes screening of many p-values with applications to microarray studies.

Datta S, Datta S.

Bioinformatics. 2005 May 1;21(9):1987-94. Epub 2005 Feb 2.

PMID:
15691856

Supplemental Content

Support Center