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Items: 1 to 20 of 122

1.

A semi-supervised method for predicting transcription factor-gene interactions in Escherichia coli.

Ernst J, Beg QK, Kay KA, Balázsi G, Oltvai ZN, Bar-Joseph Z.

PLoS Comput Biol. 2008 Mar 28;4(3):e1000044. doi: 10.1371/journal.pcbi.1000044.

2.

SIRENE: supervised inference of regulatory networks.

Mordelet F, Vert JP.

Bioinformatics. 2008 Aug 15;24(16):i76-82. doi: 10.1093/bioinformatics/btn273.

3.

Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities.

Fu Y, Jarboe LR, Dickerson JA.

BMC Bioinformatics. 2011 Jun 13;12:233. doi: 10.1186/1471-2105-12-233.

4.

Reconstruction of Escherichia coli transcriptional regulatory networks via regulon-based associations.

Zare H, Sangurdekar D, Srivastava P, Kaveh M, Khodursky A.

BMC Syst Biol. 2009 Apr 14;3:39. doi: 10.1186/1752-0509-3-39.

5.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

Marbach D, Roy S, Ay F, Meyer PE, Candeias R, Kahveci T, Bristow CA, Kellis M.

Genome Res. 2012 Jul;22(7):1334-49. doi: 10.1101/gr.127191.111. Epub 2012 Mar 28.

6.

The comprehensive updated regulatory network of Escherichia coli K-12.

Salgado H, Santos-Zavaleta A, Gama-Castro S, Peralta-Gil M, Peñaloza-Spínola MI, Martínez-Antonio A, Karp PD, Collado-Vides J.

BMC Bioinformatics. 2006 Jan 6;7:5.

7.

Hypothesis-driven approach to predict transcriptional units from gene expression data.

Steinhauser D, Junker BH, Luedemann A, Selbig J, Kopka J.

Bioinformatics. 2004 Aug 12;20(12):1928-39. Epub 2004 Mar 25.

PMID:
15044239
8.

Prediction of regulatory networks: genome-wide identification of transcription factor targets from gene expression data.

Qian J, Lin J, Luscombe NM, Yu H, Gerstein M.

Bioinformatics. 2003 Oct 12;19(15):1917-26.

PMID:
14555624
9.

FNR and its role in oxygen-regulated gene expression in Escherichia coli.

Spiro S, Guest JR.

FEMS Microbiol Rev. 1990 Aug;6(4):399-428. Review.

PMID:
2248796
10.

Discovering functional gene expression patterns in the metabolic network of Escherichia coli with wavelets transforms.

König R, Schramm G, Oswald M, Seitz H, Sager S, Zapatka M, Reinelt G, Eils R.

BMC Bioinformatics. 2006 Mar 8;7:119.

11.
12.

Gene networks inference using dynamic Bayesian networks.

Perrin BE, Ralaivola L, Mazurie A, Bottani S, Mallet J, d'Alché-Buc F.

Bioinformatics. 2003 Oct;19 Suppl 2:ii138-48.

PMID:
14534183
13.

Inferring a transcriptional regulatory network from gene expression data using nonlinear manifold embedding.

Zare H, Kaveh M, Khodursky A.

PLoS One. 2011;6(8):e21969. doi: 10.1371/journal.pone.0021969. Epub 2011 Aug 12.

14.

Predicting bacterial transcription units using sequence and expression data.

Bockhorst J, Qiu Y, Glasner J, Liu M, Blattner F, Craven M.

Bioinformatics. 2003;19 Suppl 1:i34-43.

PMID:
12855435
15.

Predicting transcriptional regulatory interactions with artificial neural networks applied to E. coli multidrug resistance efflux pumps.

Veiga DF, Vicente FF, Nicolás MF, Vasconcelos AT.

BMC Microbiol. 2008 Jun 19;8:101. doi: 10.1186/1471-2180-8-101.

16.
17.

Determining effects of non-synonymous SNPs on protein-protein interactions using supervised and semi-supervised learning.

Zhao N, Han JG, Shyu CR, Korkin D.

PLoS Comput Biol. 2014 May 1;10(5):e1003592. doi: 10.1371/journal.pcbi.1003592. eCollection 2014 May.

19.

Bayesian network expansion identifies new ROS and biofilm regulators.

Hodges AP, Dai D, Xiang Z, Woolf P, Xi C, He Y.

PLoS One. 2010 Mar 3;5(3):e9513. doi: 10.1371/journal.pone.0009513.

20.

Integrative inference of gene-regulatory networks in Escherichia coli using information theoretic concepts and sequence analysis.

Kaleta C, Göhler A, Schuster S, Jahreis K, Guthke R, Nikolajewa S.

BMC Syst Biol. 2010 Aug 18;4:116. doi: 10.1186/1752-0509-4-116.

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