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Items: 20

1.

Autophagy suppresses Ras-driven epithelial tumourigenesis by limiting the accumulation of reactive oxygen species.

Manent J, Banerjee S, de Matos Simoes R, Zoranovic T, Mitsiades C, Penninger JM, Simpson KJ, Humbert PO, Richardson HE.

Oncogene. 2017 Oct 5;36(40):5658-5660. doi: 10.1038/onc.2017.239.

PMID:
28980625
2.

Analytical Strategy to Prioritize Alzheimer's Disease Candidate Genes in Gene Regulatory Networks Using Public Expression Data.

Kawalia SB, Raschka T, Naz M, de Matos Simoes R, Senger P, Hofmann-Apitius M.

J Alzheimers Dis. 2017;59(4):1237-1254. doi: 10.3233/JAD-170011.

3.

Autophagy suppresses Ras-driven epithelial tumourigenesis by limiting the accumulation of reactive oxygen species.

Manent J, Banerjee S, de Matos Simoes R, Zoranovic T, Mitsiades C, Penninger JM, Simpson KJ, Humbert PO, Richardson HE.

Oncogene. 2017 Oct 5;36(40):5576-5592. doi: 10.1038/onc.2017.175. Epub 2017 Jun 5. Erratum in: Oncogene. 2017 Oct 5;36(40):5658-5660.

4.

samExploreR: exploring reproducibility and robustness of RNA-seq results based on SAM files.

Stupnikov A, Tripathi S, de Matos Simoes R, McArt D, Salto-Tellez M, Glazko G, Dehmer M, Emmert-Streib F.

Bioinformatics. 2016 Nov 1;32(21):3345-3347. Epub 2016 Jul 10.

PMID:
27402900
5.

NF-κB dysregulation in multiple myeloma.

Matthews GM, de Matos Simoes R, Dhimolea E, Sheffer M, Gandolfi S, Dashevsky O, Sorrell JD, Mitsiades CS.

Semin Cancer Biol. 2016 Aug;39:68-76. doi: 10.1016/j.semcancer.2016.08.005. Epub 2016 Aug 17. Review.

PMID:
27544796
6.

A BRCA1 deficient, NFκB driven immune signal predicts good outcome in triple negative breast cancer.

Buckley NE, Haddock P, De Matos Simoes R, Parkes E, Irwin G, Emmert-Streib F, McQuaid S, Kennedy R, Mullan P.

Oncotarget. 2016 Apr 12;7(15):19884-96. doi: 10.18632/oncotarget.7865.

7.

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data.

de Matos Simoes R, Dalleau S, Williamson KE, Emmert-Streib F.

BMC Syst Biol. 2015 May 14;9:21. doi: 10.1186/s12918-015-0165-z.

8.

Functional and genetic analysis of the colon cancer network.

Emmert-Streib F, de Matos Simoes R, Glazko G, McDade S, Haibe-Kains B, Holzinger A, Dehmer M, Campbell F.

BMC Bioinformatics. 2014;15 Suppl 6:S6. doi: 10.1186/1471-2105-15-S6-S6. Epub 2014 May 16.

9.

The gene regulatory network for breast cancer: integrated regulatory landscape of cancer hallmarks.

Emmert-Streib F, de Matos Simoes R, Mullan P, Haibe-Kains B, Dehmer M.

Front Genet. 2014 Feb 3;5:15. doi: 10.3389/fgene.2014.00015. eCollection 2014.

10.

B-cell lymphoma gene regulatory networks: biological consistency among inference methods.

de Matos Simoes R, Dehmer M, Emmert-Streib F.

Front Genet. 2013 Dec 16;4:281. doi: 10.3389/fgene.2013.00281. eCollection 2013.

11.

Interfacing cellular networks of S. cerevisiae and E. coli: connecting dynamic and genetic information.

de Matos Simoes R, Dehmer M, Emmert-Streib F.

BMC Genomics. 2013 May 11;14:324. doi: 10.1186/1471-2164-14-324.

12.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data.

Emmert-Streib F, Abogunrin F, de Matos Simoes R, Duggan B, Ruddock MW, Reid CN, Roddy O, White L, O'Kane HF, O'Rourke D, Anderson NH, Nambirajan T, Williamson KE.

BMC Med. 2013 Jan 17;11:12. doi: 10.1186/1741-7015-11-12.

13.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods.

Emmert-Streib F, Tripathi S, de Matos Simoes R.

Biol Direct. 2012 Dec 10;7:44. doi: 10.1186/1745-6150-7-44. Review.

14.

A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data.

Emmert-Streib F, de Matos Simoes R, Tripathi S, Glazko GV, Dehmer M.

Sci Rep. 2012;2:513. doi: 10.1038/srep00513. Epub 2012 Jul 20.

15.

Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma.

de Matos Simoes R, Tripathi S, Emmert-Streib F.

BMC Syst Biol. 2012 May 14;6:38. doi: 10.1186/1752-0509-6-38.

16.

Bagging statistical network inference from large-scale gene expression data.

de Matos Simoes R, Emmert-Streib F.

PLoS One. 2012;7(3):e33624. doi: 10.1371/journal.pone.0033624. Epub 2012 Mar 30.

17.

Statistical inference and reverse engineering of gene regulatory networks from observational expression data.

Emmert-Streib F, Glazko GV, Altay G, de Matos Simoes R.

Front Genet. 2012 Feb 3;3:8. doi: 10.3389/fgene.2012.00008. eCollection 2012.

18.

Influence of statistical estimators of mutual information and data heterogeneity on the inference of gene regulatory networks.

de Matos Simoes R, Emmert-Streib F.

PLoS One. 2011;6(12):e29279. doi: 10.1371/journal.pone.0029279. Epub 2011 Dec 29.

19.

A consistent phylogenetic backbone for the fungi.

Ebersberger I, de Matos Simoes R, Kupczok A, Gube M, Kothe E, Voigt K, von Haeseler A.

Mol Biol Evol. 2012 May;29(5):1319-34. doi: 10.1093/molbev/msr285. Epub 2011 Nov 22.

20.

A Mek1-Mek2 heterodimer determines the strength and duration of the Erk signal.

Catalanotti F, Reyes G, Jesenberger V, Galabova-Kovacs G, de Matos Simoes R, Carugo O, Baccarini M.

Nat Struct Mol Biol. 2009 Mar;16(3):294-303. doi: 10.1038/nsmb.1564. Epub 2009 Feb 15.

PMID:
19219045

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