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Items: 1 to 20 of 88

1.

Evidence of highly regulated genes (in-Hubs) in gene networks of Saccharomyces cerevisiae.

Lundström J, Björkegren J, Tegnér J.

Bioinform Biol Insights. 2008 Jul 14;2:307-16.

2.

Stratus not altocumulus: a new view of the yeast protein interaction network.

Batada NN, Reguly T, Breitkreutz A, Boucher L, Breitkreutz BJ, Hurst LD, Tyers M.

PLoS Biol. 2006 Oct;4(10):e317.

3.

Genome-wide system analysis reveals stable yet flexible network dynamics in yeast.

Gustafsson M, Hörnquist M, Björkegren J, Tegnér J.

IET Syst Biol. 2009 Jul;3(4):219-28. doi: 10.1049/iet-syb.2008.0112.

PMID:
19640161
4.

Understanding gene essentiality by finely characterizing hubs in the yeast protein interaction network.

Pang K, Sheng H, Ma X.

Biochem Biophys Res Commun. 2010 Oct 8;401(1):112-6. doi: 10.1016/j.bbrc.2010.09.021. Epub 2010 Sep 15.

PMID:
20833129
5.

Protein evolution in yeast transcription factor subnetworks.

Wang Y, Franzosa EA, Zhang XS, Xia Y.

Nucleic Acids Res. 2010 Oct;38(18):5959-69. doi: 10.1093/nar/gkq353. Epub 2010 May 13.

6.
7.

Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle.

Bushel PR, Heard NA, Gutman R, Liu L, Peddada SD, Pyne S.

BMC Syst Biol. 2009 Sep 16;3:93. doi: 10.1186/1752-0509-3-93.

9.

Correlation of genomic features with dynamic modularity in the yeast interactome: a view from the structural perspective.

Wang H, Zheng H.

IEEE Trans Nanobioscience. 2012 Sep;11(3):244-50. doi: 10.1109/TNB.2012.2212720.

PMID:
22987130
10.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

Muetze T, Goenawan IH, Wiencko HL, Bernal-Llinares M, Bryan K, Lynn DJ.

Version 2. F1000Res. 2016 Jul 19 [revised 2016 Jan 1];5:1745. eCollection 2016.

11.

Dynamic hubs show competitive and static hubs non-competitive regulation of their interaction partners.

Goel A, Wilkins MR.

PLoS One. 2012;7(10):e48209. doi: 10.1371/journal.pone.0048209. Epub 2012 Oct 31.

12.
13.

TimeDelay-ARACNE: Reverse engineering of gene networks from time-course data by an information theoretic approach.

Zoppoli P, Morganella S, Ceccarelli M.

BMC Bioinformatics. 2010 Mar 25;11:154. doi: 10.1186/1471-2105-11-154.

14.

The properties of hub proteins in a yeast-aggregated cell cycle network and its phase sub-networks.

Wu X, Guo J, Zhang DY, Lin K.

Proteomics. 2009 Oct;9(20):4812-24. doi: 10.1002/pmic.200900053.

PMID:
19743420
15.

Inferring a transcriptional regulatory network of the cytokinesis-related genes by network component analysis.

Chen SF, Juang YL, Chou WK, Lai JM, Huang CY, Kao CY, Wang FS.

BMC Syst Biol. 2009 Nov 27;3:110. doi: 10.1186/1752-0509-3-110.

16.

Identification of functional hubs and modules by converting interactome networks into hierarchical ordering of proteins.

Cho YR, Zhang A.

BMC Bioinformatics. 2010 Apr 29;11 Suppl 3:S3. doi: 10.1186/1471-2105-11-S3-S3.

17.

Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach.

Bailly-Bechet M, Braunstein A, Pagnani A, Weigt M, Zecchina R.

BMC Bioinformatics. 2010 Jun 29;11:355. doi: 10.1186/1471-2105-11-355.

18.

Bottlenecks and hubs in inferred networks are important for virulence in Salmonella typhimurium.

McDermott JE, Taylor RC, Yoon H, Heffron F.

J Comput Biol. 2009 Feb;16(2):169-80. doi: 10.1089/cmb.2008.04TT.

PMID:
19178137
19.

Computational discovery of gene modules and regulatory networks.

Bar-Joseph Z, Gerber GK, Lee TI, Rinaldi NJ, Yoo JY, Robert F, Gordon DB, Fraenkel E, Jaakkola TS, Young RA, Gifford DK.

Nat Biotechnol. 2003 Nov;21(11):1337-42. Epub 2003 Oct 12.

20.

A predictive model of the oxygen and heme regulatory network in yeast.

Kundaje A, Xin X, Lan C, Lianoglou S, Zhou M, Zhang L, Leslie C.

PLoS Comput Biol. 2008 Nov;4(11):e1000224. doi: 10.1371/journal.pcbi.1000224. Epub 2008 Nov 14.

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