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Items: 1 to 20 of 125

1.

Discovering biological connections between experimental conditions based on common patterns of differential gene expression.

Gower AC, Spira A, Lenburg ME.

BMC Bioinformatics. 2011 Sep 27;12:381. doi: 10.1186/1471-2105-12-381.

2.

Hormone receptor and ERBB2 status in gene expression profiles of human breast tumor samples.

Dvorkin-Gheva A, Hassell JA.

PLoS One. 2011;6(10):e26023. doi: 10.1371/journal.pone.0026023. Epub 2011 Oct 13.

3.

Meta-analysis of breast cancer microarray studies in conjunction with conserved cis-elements suggest patterns for coordinate regulation.

Smith DD, Saetrom P, Snøve O Jr, Lundberg C, Rivas GE, Glackin C, Larson GP.

BMC Bioinformatics. 2008 Jan 28;9:63. doi: 10.1186/1471-2105-9-63.

4.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

Feng C, Araki M, Kunimoto R, Tamon A, Makiguchi H, Niijima S, Tsujimoto G, Okuno Y.

BMC Genomics. 2009 Sep 3;10:411. doi: 10.1186/1471-2164-10-411.

5.

Content-based microarray search using differential expression profiles.

Engreitz JM, Morgan AA, Dudley JT, Chen R, Thathoo R, Altman RB, Butte AJ.

BMC Bioinformatics. 2010 Dec 21;11:603. doi: 10.1186/1471-2105-11-603.

7.

MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures.

Vazquez M, Nogales-Cadenas R, Arroyo J, Botías P, García R, Carazo JM, Tirado F, Pascual-Montano A, Carmona-Saez P.

Nucleic Acids Res. 2010 Jul;38(Web Server issue):W228-32. doi: 10.1093/nar/gkq476. Epub 2010 May 31.

8.

Molecular identification of ERalpha-positive breast cancer cells by the expression profile of an intrinsic set of estrogen regulated genes.

Weisz A, Basile W, Scafoglio C, Altucci L, Bresciani F, Facchiano A, Sismondi P, Cicatiello L, De Bortoli M.

J Cell Physiol. 2004 Sep;200(3):440-50.

PMID:
15254972
9.

T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers.

Rody A, Holtrich U, Pusztai L, Liedtke C, Gaetje R, Ruckhaeberle E, Solbach C, Hanker L, Ahr A, Metzler D, Engels K, Karn T, Kaufmann M.

Breast Cancer Res. 2009;11(2):R15. doi: 10.1186/bcr2234. Epub 2009 Mar 9.

10.

Meta-analysis and gene set enrichment relative to er status reveal elevated activity of MYC and E2F in the "basal" breast cancer subgroup.

Alles MC, Gardiner-Garden M, Nott DJ, Wang Y, Foekens JA, Sutherland RL, Musgrove EA, Ormandy CJ.

PLoS One. 2009;4(3):e4710. doi: 10.1371/journal.pone.0004710. Epub 2009 Mar 9.

11.

ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression.

Engreitz JM, Chen R, Morgan AA, Dudley JT, Mallelwar R, Butte AJ.

Bioinformatics. 2011 Dec 1;27(23):3317-8. doi: 10.1093/bioinformatics/btr548. Epub 2011 Oct 3.

12.

The gene expression response of breast cancer to growth regulators: patterns and correlation with tumor expression profiles.

Cunliffe HE, Ringnér M, Bilke S, Walker RL, Cheung JM, Chen Y, Meltzer PS.

Cancer Res. 2003 Nov 1;63(21):7158-66.

13.

mRNA expression profiles show differential regulatory effects of microRNAs between estrogen receptor-positive and estrogen receptor-negative breast cancer.

Cheng C, Fu X, Alves P, Gerstein M.

Genome Biol. 2009;10(9):R90. doi: 10.1186/gb-2009-10-9-r90. Epub 2009 Sep 1.

14.

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

Grigoriadis A, Mackay A, Reis-Filho JS, Steele D, Iseli C, Stevenson BJ, Jongeneel CV, Valgeirsson H, Fenwick K, Iravani M, Leao M, Simpson AJ, Strausberg RL, Jat PS, Ashworth A, Neville AM, O'Hare MJ.

Breast Cancer Res. 2006;8(5):R56.

15.

Evaluation of public cancer datasets and signatures identifies TP53 mutant signatures with robust prognostic and predictive value.

Lehmann BD, Ding Y, Viox DJ, Jiang M, Zheng Y, Liao W, Chen X, Xiang W, Yi Y.

BMC Cancer. 2015 Mar 26;15:179. doi: 10.1186/s12885-015-1102-7.

16.

A gene transcription signature of obesity in breast cancer.

Creighton CJ, Sada YH, Zhang Y, Tsimelzon A, Wong H, Dave B, Landis MD, Bear HD, Rodriguez A, Chang JC.

Breast Cancer Res Treat. 2012 Apr;132(3):993-1000. doi: 10.1007/s10549-011-1595-y. Epub 2011 Jul 13.

PMID:
21750966
17.

Query large scale microarray compendium datasets using a model-based bayesian approach with variable selection.

Hu M, Qin ZS.

PLoS One. 2009;4(2):e4495. doi: 10.1371/journal.pone.0004495. Epub 2009 Feb 13.

18.

An integrated bioinformatics approach identifies elevated cyclin E2 expression and E2F activity as distinct features of tamoxifen resistant breast tumors.

Huang L, Zhao S, Frasor JM, Dai Y.

PLoS One. 2011;6(7):e22274. doi: 10.1371/journal.pone.0022274. Epub 2011 Jul 15.

19.

Lack of sufficiently strong informative features limits the potential of gene expression analysis as predictive tool for many clinical classification problems.

Hess KR, Wei C, Qi Y, Iwamoto T, Symmans WF, Pusztai L.

BMC Bioinformatics. 2011 Dec 1;12:463. doi: 10.1186/1471-2105-12-463.

20.

A novel method for generation of signature networks as biomarkers from complex high throughput data.

Nikolsky Y, Ekins S, Nikolskaya T, Bugrim A.

Toxicol Lett. 2005 Jul 28;158(1):20-9.

PMID:
15871913

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