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Items: 1 to 20 of 79

1.

Discovering transcriptional modules by Bayesian data integration.

Savage RS, Ghahramani Z, Griffin JE, de la Cruz BJ, Wild DL.

Bioinformatics. 2010 Jun 15;26(12):i158-67. doi: 10.1093/bioinformatics/btq210.

2.

A Gibbs sampler for the identification of gene expression and network connectivity consistency.

Brynildsen MP, Tran LM, Liao JC.

Bioinformatics. 2006 Dec 15;22(24):3040-6. Epub 2006 Oct 23.

PMID:
17060361
3.

Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model.

Youn A, Reiss DJ, Stuetzle W.

Bioinformatics. 2010 Aug 1;26(15):1879-86. doi: 10.1093/bioinformatics/btq289. Epub 2010 Jun 4.

4.
5.

Defining transcription modules using large-scale gene expression data.

Ihmels J, Bergmann S, Barkai N.

Bioinformatics. 2004 Sep 1;20(13):1993-2003. Epub 2004 Mar 25.

PMID:
15044247
6.

Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data.

Liu X, Jessen WJ, Sivaganesan S, Aronow BJ, Medvedovic M.

BMC Bioinformatics. 2007 Aug 3;8:283.

7.

Bayesian sparse hidden components analysis for transcription regulation networks.

Sabatti C, James GM.

Bioinformatics. 2006 Mar 15;22(6):739-46. Epub 2005 Dec 20.

PMID:
16368767
8.

Transcriptome network component analysis with limited microarray data.

Galbraith SJ, Tran LM, Liao JC.

Bioinformatics. 2006 Aug 1;22(15):1886-94. Epub 2006 Jun 9.

PMID:
16766556
9.

Integrating genomic data to predict transcription factor binding.

Holloway DT, Kon M, DeLisi C.

Genome Inform. 2005;16(1):83-94.

PMID:
16362910
10.

Inference of combinatorial regulation in yeast transcriptional networks: a case study of sporulation.

Wang W, Cherry JM, Nochomovitz Y, Jolly E, Botstein D, Li H.

Proc Natl Acad Sci U S A. 2005 Feb 8;102(6):1998-2003. Epub 2005 Jan 31.

11.

A Bayesian approach to reconstructing genetic regulatory networks with hidden factors.

Beal MJ, Falciani F, Ghahramani Z, Rangel C, Wild DL.

Bioinformatics. 2005 Feb 1;21(3):349-56. Epub 2004 Sep 7.

PMID:
15353451
12.
13.

Using local gene expression similarities to discover regulatory binding site modules.

WilczyƄski B, Hvidsten TR, Kryshtafovych A, Tiuryn J, Komorowski J, Fidelis K.

BMC Bioinformatics. 2006 Nov 17;7:505.

14.
15.

Clustering of change patterns using Fourier coefficients.

Kim J, Kim H.

Bioinformatics. 2008 Jan 15;24(2):184-91. Epub 2007 Nov 19.

PMID:
18025003
16.

Analysis of a Gibbs sampler method for model-based clustering of gene expression data.

Joshi A, Van de Peer Y, Michoel T.

Bioinformatics. 2008 Jan 15;24(2):176-83. Epub 2007 Nov 22.

PMID:
18033794
17.

Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data.

Zhang Y, Xuan J, de los Reyes BG, Clarke R, Ressom HW.

BMC Bioinformatics. 2008 Apr 21;9:203. doi: 10.1186/1471-2105-9-203.

18.

Detecting functional modules in the yeast protein-protein interaction network.

Chen J, Yuan B.

Bioinformatics. 2006 Sep 15;22(18):2283-90. Epub 2006 Jul 12.

PMID:
16837529
19.

Inferring genetic regulatory logic from expression data.

Bulashevska S, Eils R.

Bioinformatics. 2005 Jun 1;21(11):2706-13. Epub 2005 Mar 22.

PMID:
15784747
20.

De novo motif discovery facilitates identification of interactions between transcription factors in Saccharomyces cerevisiae.

Chen MJ, Chou LC, Hsieh TT, Lee DD, Liu KW, Yu CY, Oyang YJ, Tsai HK, Chen CY.

Bioinformatics. 2012 Mar 1;28(5):701-8. doi: 10.1093/bioinformatics/bts002. Epub 2012 Jan 11.

PMID:
22238267

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