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Items: 1 to 20 of 109

1.

Model averaging strategies for structure learning in Bayesian networks with limited data.

Broom BM, Do KA, Subramanian D.

BMC Bioinformatics. 2012;13 Suppl 13:S10. doi: 10.1186/1471-2105-13-S13-S10. Epub 2012 Aug 24.

2.

Impact of censoring on learning Bayesian networks in survival modelling.

Stajduhar I, Dalbelo-Basić B, Bogunović N.

Artif Intell Med. 2009 Nov;47(3):199-217. doi: 10.1016/j.artmed.2009.08.001. Epub 2009 Oct 14.

PMID:
19833488
3.

Empirical evaluation of scoring functions for Bayesian network model selection.

Liu Z, Malone B, Yuan C.

BMC Bioinformatics. 2012;13 Suppl 15:S14. doi: 10.1186/1471-2105-13-S15-S14. Epub 2012 Sep 11.

4.

SAGA: a hybrid search algorithm for Bayesian Network structure learning of transcriptional regulatory networks.

Adabor ES, Acquaah-Mensah GK, Oduro FT.

J Biomed Inform. 2015 Feb;53:27-35. doi: 10.1016/j.jbi.2014.08.010. Epub 2014 Aug 30.

5.

Structure learning for Bayesian networks as models of biological networks.

Larjo A, Shmulevich I, Lähdesmäki H.

Methods Mol Biol. 2013;939:35-45. doi: 10.1007/978-1-62703-107-3_4.

PMID:
23192539
6.

Bayesian model averaging of naive Bayes for clustering.

Santafé G, Lozano JA, Larrañaga P.

IEEE Trans Syst Man Cybern B Cybern. 2006 Oct;36(5):1149-61.

PMID:
17036820
7.

A Bayesian network classification methodology for gene expression data.

Helman P, Veroff R, Atlas SR, Willman C.

J Comput Biol. 2004;11(4):581-615.

PMID:
15579233
8.

Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.

Tong DL, Schierz AC.

Artif Intell Med. 2011 Sep;53(1):47-56. doi: 10.1016/j.artmed.2011.06.008. Epub 2011 Jul 19.

PMID:
21775110
9.

A hybrid Bayesian network learning method for constructing gene networks.

Wang M, Chen Z, Cloutier S.

Comput Biol Chem. 2007 Oct;31(5-6):361-72. Epub 2007 Aug 19.

PMID:
17889617
10.

Learning the structure of gene regulatory networks from time series gene expression data.

Li H, Wang N, Gong P, Perkins EJ, Zhang C.

BMC Genomics. 2011 Dec 23;12 Suppl 5:S13. doi: 10.1186/1471-2164-12-S5-S13. Epub 2011 Dec 23.

11.

Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data.

Gao S, Wang X.

BMC Bioinformatics. 2011 Aug 31;12:359. doi: 10.1186/1471-2105-12-359.

12.

H-CORE: enabling genome-scale Bayesian analysis of biological systems without prior knowledge.

Jung S, Lee KH, Lee D.

Biosystems. 2007 Jul-Aug;90(1):197-210. Epub 2006 Aug 22.

PMID:
17005318
13.

Reconstruction of gene networks using Bayesian learning and manipulation experiments.

Pournara I, Wernisch L.

Bioinformatics. 2004 Nov 22;20(17):2934-42. Epub 2004 Jun 4.

PMID:
15180938
14.

An effective structure learning method for constructing gene networks.

Chen XW, Anantha G, Wang X.

Bioinformatics. 2006 Jun 1;22(11):1367-74. Epub 2006 Mar 16.

PMID:
16543279
15.

Using stochastic causal trees to augment Bayesian networks for modeling eQTL datasets.

Chipman KC, Singh AK.

BMC Bioinformatics. 2011 Jan 6;12:7. doi: 10.1186/1471-2105-12-7.

16.

Context-specific gene regulations in cancer gene expression data.

Sen I, Verdicchio MP, Jung S, Trevino R, Bittner M, Kim S.

Pac Symp Biocomput. 2009:75-86.

17.

Bayesian unsupervised learning with multiple data types.

Agius P, Ying Y, Campbell C.

Stat Appl Genet Mol Biol. 2009;8:Article27. doi: 10.2202/1544-6115.1441. Epub 2009 Jun 5. Review.

PMID:
19572826
18.

Joint learning of gene functions--a Bayesian network model approach.

Deng X, Geng H, Ali HH.

J Bioinform Comput Biol. 2006 Apr;4(2):217-39.

PMID:
16819781
19.

Learning Bayesian networks for clinical time series analysis.

van der Heijden M, Velikova M, Lucas PJ.

J Biomed Inform. 2014 Apr;48:94-105. doi: 10.1016/j.jbi.2013.12.007. Epub 2013 Dec 18.

20.

Incorporating expert knowledge when learning Bayesian network structure: a medical case study.

Julia Flores M, Nicholson AE, Brunskill A, Korb KB, Mascaro S.

Artif Intell Med. 2011 Nov;53(3):181-204. doi: 10.1016/j.artmed.2011.08.004. Epub 2011 Sep 29.

PMID:
21958683

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