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Items: 1 to 20 of 250

1.
2.

Gene co-expression modules as clinically relevant hallmarks of breast cancer diversity.

Wolf DM, Lenburg ME, Yau C, Boudreau A, van 't Veer LJ.

PLoS One. 2014 Feb 7;9(2):e88309. doi: 10.1371/journal.pone.0088309. eCollection 2014.

3.

A modular analysis of breast cancer reveals a novel low-grade molecular signature in estrogen receptor-positive tumors.

Yu K, Ganesan K, Miller LD, Tan P.

Clin Cancer Res. 2006 Jun 1;12(11 Pt 1):3288-96.

4.

The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition.

Fredlund E, Staaf J, Rantala JK, Kallioniemi O, Borg A, Ringnér M.

Breast Cancer Res. 2012 Jul 27;14(4):R113. doi: 10.1186/bcr3236.

5.

An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer.

Xu M, Kao MC, Nunez-Iglesias J, Nevins JR, West M, Zhou XJ.

BMC Genomics. 2008;9 Suppl 1:S12. doi: 10.1186/1471-2164-9-S1-S12.

6.

Correlating transcriptional networks with pathological complete response following neoadjuvant chemotherapy for breast cancer.

Liu R, Lv QL, Yu J, Hu L, Zhang LH, Cheng Y, Zhou HH.

Breast Cancer Res Treat. 2015 Jun;151(3):607-18. doi: 10.1007/s10549-015-3428-x. Epub 2015 May 16.

PMID:
25981901
7.
8.

Gene set-based module discovery in the breast cancer transcriptome.

Niida A, Smith AD, Imoto S, Aburatani H, Zhang MQ, Akiyama T.

BMC Bioinformatics. 2009 Feb 26;10:71. doi: 10.1186/1471-2105-10-71.

9.

miRNA-mRNA correlation-network modules in human prostate cancer and the differences between primary and metastatic tumor subtypes.

Zhang W, Edwards A, Fan W, Flemington EK, Zhang K.

PLoS One. 2012;7(6):e40130. doi: 10.1371/journal.pone.0040130. Epub 2012 Jun 29.

10.

Motif-guided sparse decomposition of gene expression data for regulatory module identification.

Gong T, Xuan J, Chen L, Riggins RB, Li H, Hoffman EP, Clarke R, Wang Y.

BMC Bioinformatics. 2011 Mar 22;12:82. doi: 10.1186/1471-2105-12-82.

11.

mAPC-GibbsOS: an integrated approach for robust identification of gene regulatory networks.

Shi X, Gu J, Chen X, Shajahan A, Hilakivi-Clarke L, Clarke R, Xuan J.

BMC Syst Biol. 2013;7 Suppl 5:S4. doi: 10.1186/1752-0509-7-S5-S4. Epub 2013 Dec 9.

12.

SAP domain-dependent Mkl1 signaling stimulates proliferation and cell migration by induction of a distinct gene set indicative of poor prognosis in breast cancer patients.

Gurbuz I, Ferralli J, Roloff T, Chiquet-Ehrismann R, Asparuhova MB.

Mol Cancer. 2014 Feb 5;13:22. doi: 10.1186/1476-4598-13-22.

13.

Identifying grade/stage-related active modules in human co-regulatory networks: a case study for breast cancer.

Feng C, Chen L, Li W, Wang H, Zhang L, Jia X, Miao Z, Qu X, Li W, He W.

OMICS. 2012 Dec;16(12):681-9. doi: 10.1089/omi.2012.0015.

14.

Incorporating motif analysis into gene co-expression networks reveals novel modular expression pattern and new signaling pathways.

Ma S, Shah S, Bohnert HJ, Snyder M, Dinesh-Kumar SP.

PLoS Genet. 2013;9(10):e1003840. doi: 10.1371/journal.pgen.1003840. Epub 2013 Oct 3.

15.

A co-expression modules based gene selection for cancer recognition.

Lu X, Deng Y, Huang L, Feng B, Liao B.

J Theor Biol. 2014 Dec 7;362:75-82. doi: 10.1016/j.jtbi.2014.01.005. Epub 2014 Jan 15.

PMID:
24440175
16.

Integrated module and gene-specific regulatory inference implicates upstream signaling networks.

Roy S, Lagree S, Hou Z, Thomson JA, Stewart R, Gasch AP.

PLoS Comput Biol. 2013;9(10):e1003252. doi: 10.1371/journal.pcbi.1003252. Epub 2013 Oct 17.

17.

Bioinformatics analysis of aggressive behavior of breast cancer via an integrated gene regulatory network.

Yang X, Jia M, Li Z, Lu S, Qi X, Zhao B, Wang X, Rong Y, Shi J, Zhang Z, Xu W, Gao Y, Zhang S, Yu G.

J Cancer Res Ther. 2014 Oct-Dec;10(4):1013-8. doi: 10.4103/0973-1482.137971.

18.

EDISA: extracting biclusters from multiple time-series of gene expression profiles.

Supper J, Strauch M, Wanke D, Harter K, Zell A.

BMC Bioinformatics. 2007 Sep 12;8:334.

19.

Elucidating the altered transcriptional programs in breast cancer using independent component analysis.

Teschendorff AE, Journée M, Absil PA, Sepulchre R, Caldas C.

PLoS Comput Biol. 2007 Aug;3(8):e161. Epub 2007 Jun 29.

20.

Module-based outcome prediction using breast cancer compendia.

van Vliet MH, Klijn CN, Wessels LF, Reinders MJ.

PLoS One. 2007 Oct 17;2(10):e1047.

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