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Items: 1 to 20 of 178

1.

Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements.

Cooke EJ, Savage RS, Kirk PD, Darkins R, Wild DL.

BMC Bioinformatics. 2011 Oct 13;12:399. doi: 10.1186/1471-2105-12-399.

2.

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.

Darkins R, Cooke EJ, Ghahramani Z, Kirk PD, Wild DL, Savage RS.

PLoS One. 2013;8(4):e59795. doi: 10.1371/journal.pone.0059795.

3.

Bayesian mixture model based clustering of replicated microarray data.

Medvedovic M, Yeung KY, Bumgarner RE.

Bioinformatics. 2004 May 22;20(8):1222-32.

PMID:
14871871
4.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

Hensman J, Lawrence ND, Rattray M.

BMC Bioinformatics. 2013 Aug 20;14:252. doi: 10.1186/1471-2105-14-252.

5.

R/BHC: fast Bayesian hierarchical clustering for microarray data.

Savage RS, Heller K, Xu Y, Ghahramani Z, Truman WM, Grant M, Denby KJ, Wild DL.

BMC Bioinformatics. 2009 Aug 6;10:242. doi: 10.1186/1471-2105-10-242.

6.

Bayesian infinite mixture model based clustering of gene expression profiles.

Medvedovic M, Sivaganesan S.

Bioinformatics. 2002 Sep;18(9):1194-206.

PMID:
12217911
7.

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics.

Sirinukunwattana K, Savage RS, Bari MF, Snead DR, Rajpoot NM.

PLoS One. 2013 Oct 23;8(10):e75748. doi: 10.1371/journal.pone.0075748.

8.

Including probe-level measurement error in robust mixture clustering of replicated microarray gene expression.

Liu X, Rattray M.

Stat Appl Genet Mol Biol. 2010;9:Article42. doi: 10.2202/1544-6115.1600.

PMID:
21194414
10.

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.

11.

Bayesian model-based clustering of temporal gene expression using autoregressive panel data approach.

Nascimento M, Sáfadi T, Fonseca e Silva F, Nascimento AC.

Bioinformatics. 2012 Aug 1;28(15):2004-7. doi: 10.1093/bioinformatics/bts322.

PMID:
22668790
12.

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.

13.

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.

PMID:
18033794
14.

Modeling and visualizing uncertainty in gene expression clusters using dirichlet process mixtures.

Rasmussen CE, de la Cruz BJ, Ghahramani Z, Wild DL.

IEEE/ACM Trans Comput Biol Bioinform. 2009 Oct-Dec;6(4):615-28. doi: 10.1109/TCBB.2007.70269.

PMID:
19875860
15.
16.

The latent process decomposition of cDNA microarray data sets.

Rogers S, Girolami M, Campbell C, Breitling R.

IEEE/ACM Trans Comput Biol Bioinform. 2005 Apr-Jun;2(2):143-56.

PMID:
17044179
17.

A mixture model with random-effects components for clustering correlated gene-expression profiles.

Ng SK, McLachlan GJ, Wang K, Ben-Tovim Jones L, Ng SW.

Bioinformatics. 2006 Jul 15;22(14):1745-52.

PMID:
16675467
18.

H-CLAP: hierarchical clustering within a linear array with an application in genetics.

Ghosh S, Townsend JP.

Stat Appl Genet Mol Biol. 2015 Apr;14(2):125-41. doi: 10.1515/sagmb-2013-0076.

PMID:
25803088
19.

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

Angelini C, Cutillo L, De Canditiis D, Mutarelli M, Pensky M.

BMC Bioinformatics. 2008 Oct 6;9:415. doi: 10.1186/1471-2105-9-415.

20.

Bayesian correlated clustering to integrate multiple datasets.

Kirk P, Griffin JE, Savage RS, Ghahramani Z, Wild DL.

Bioinformatics. 2012 Dec 15;28(24):3290-7. doi: 10.1093/bioinformatics/bts595.

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