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Items: 1 to 20 of 58

1.

Bayesian gene set analysis for identifying significant biological pathways.

Shahbaba B, Tibshirani R, Shachaf CM, Plevritis SK.

J R Stat Soc Ser C Appl Stat. 2011 Aug 1;60(4):541-557.

2.

INCORPORATING BIOLOGICAL INFORMATION INTO LINEAR MODELS: A BAYESIAN APPROACH TO THE SELECTION OF PATHWAYS AND GENES.

Stingo FC, Chen YA, Tadesse MG, Vannucci M.

Ann Appl Stat. 2011 Sep 1;5(3):1978-2002.

3.
4.

Improving gene set analysis of microarray data by SAM-GS.

Dinu I, Potter JD, Mueller T, Liu Q, Adewale AJ, Jhangri GS, Einecke G, Famulski KS, Halloran P, Yasui Y.

BMC Bioinformatics. 2007 Jul 5;8:242.

5.

A pathway analysis method for genome-wide association studies.

Shahbaba B, Shachaf CM, Yu Z.

Stat Med. 2012 May 10;31(10):988-1000. doi: 10.1002/sim.4477. Epub 2012 Feb 3.

PMID:
22302470
6.

Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments.

Zhao H, Chan KL, Cheng LM, Yan H.

BMC Bioinformatics. 2008;9 Suppl 1:S9. doi: 10.1186/1471-2105-9-S1-S9.

7.

Biological and functional analysis of statistically significant pathways deregulated in colon cancer by using gene expression profiles.

Distaso A, Abatangelo L, Maglietta R, Creanza TM, Piepoli A, Carella M, D'Addabbo A, Ancona N.

Int J Biol Sci. 2008;4(6):368-78. Epub 2008 Oct 14.

8.

A route-based pathway analysis framework integrating mutation information and gene expression data.

Zhao Y, Hoang TH, Joshi P, Hong SH, Giardina C, Shin DG.

Methods. 2017 Jul 15;124:3-12. doi: 10.1016/j.ymeth.2017.06.016. Epub 2017 Jun 22.

PMID:
28647608
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11.

Bayesian methods for expression-based integration of various types of genomics data.

Jennings EM, Morris JS, Carroll RJ, Manyam GC, Baladandayuthapani V.

EURASIP J Bioinform Syst Biol. 2013 Sep 21;2013(1):13. doi: 10.1186/1687-4153-2013-13.

12.

Pathway-based Bayesian inference of drug-disease interactions.

Pratanwanich N, LiĆ³ P.

Mol Biosyst. 2014 Jun;10(6):1538-48. doi: 10.1039/c4mb00014e. Epub 2014 Apr 3.

PMID:
24695945
13.

Efficient methods for identifying mutated driver pathways in cancer.

Zhao J, Zhang S, Wu LY, Zhang XS.

Bioinformatics. 2012 Nov 15;28(22):2940-7. doi: 10.1093/bioinformatics/bts564. Epub 2012 Sep 14.

PMID:
22982574
14.

A phase synchronization clustering algorithm for identifying interesting groups of genes from cell cycle expression data.

Kim CS, Bae CS, Tcha HJ.

BMC Bioinformatics. 2008 Jan 28;9:56. doi: 10.1186/1471-2105-9-56.

16.

Gene expression patterns associated with p53 status in breast cancer.

Troester MA, Herschkowitz JI, Oh DS, He X, Hoadley KA, Barbier CS, Perou CM.

BMC Cancer. 2006 Dec 6;6:276.

17.

New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data.

Parikh A, Huang E, Dinh C, Zupan B, Kuspa A, Subramanian D, Shaulsky G.

BMC Bioinformatics. 2010 Mar 31;11:163. doi: 10.1186/1471-2105-11-163.

18.

Carbon sequestration in Synechococcus Sp.: from molecular machines to hierarchical modeling.

Heffelfinger GS, Martino A, Gorin A, Xu Y, Rintoul MD 3rd, Geist A, Al-Hashimi HM, Davidson GS, Faulon JL, Frink LJ, Haaland DM, Hart WE, Jakobsson E, Lane T, Li M, Locascio P, Olken F, Olman V, Palenik B, Plimpton SJ, Roe DC, Samatova NF, Shah M, Shoshoni A, Strauss CE, Thomas EV, Timlin JA, Xu D.

OMICS. 2002;6(4):305-30.

19.

Identification of mutated core cancer modules by integrating somatic mutation, copy number variation, and gene expression data.

Zhang J, Zhang S, Wang Y, Zhang XS.

BMC Syst Biol. 2013;7 Suppl 2:S4. doi: 10.1186/1752-0509-7-S2-S4. Epub 2013 Oct 14.

20.

Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments.

Sartor MA, Tomlinson CR, Wesselkamper SC, Sivaganesan S, Leikauf GD, Medvedovic M.

BMC Bioinformatics. 2006 Dec 19;7:538.

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