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Items: 1 to 20 of 54

1.

Towards revealing the functions of all genes in plants.

Rhee SY, Mutwil M.

Trends Plant Sci. 2014 Apr;19(4):212-21. doi: 10.1016/j.tplants.2013.10.006. Epub 2013 Nov 11. Review.

PMID:
24231067
2.

Inferring gene functions through dissection of relevance networks: interleaving the intra- and inter-species views.

Klie S, Mutwil M, Persson S, Nikoloski Z.

Mol Biosyst. 2012 Sep;8(9):2233-41. Epub 2012 Jun 29. Review.

PMID:
22744313
3.

Computational inference of gene regulatory networks: Approaches, limitations and opportunities.

Banf M, Rhee SY.

Biochim Biophys Acta Gene Regul Mech. 2017 Jan;1860(1):41-52. doi: 10.1016/j.bbagrm.2016.09.003. Epub 2016 Sep 16. Review.

PMID:
27641093
4.

Biostatistical approaches for the reconstruction of gene co-expression networks based on transcriptomic data.

López-Kleine L, Leal L, López C.

Brief Funct Genomics. 2013 Sep;12(5):457-67. doi: 10.1093/bfgp/elt003. Epub 2013 Feb 12. Review.

PMID:
23407269
5.

Gene expression complex networks: synthesis, identification, and analysis.

Lopes FM, Cesar RM, Costa Lda F.

J Comput Biol. 2011 Oct;18(10):1353-67. doi: 10.1089/cmb.2010.0118. Epub 2011 May 6.

PMID:
21548810
6.

Discovering functions and revealing mechanisms at molecular level from biological networks.

Zhang S, Jin G, Zhang XS, Chen L.

Proteomics. 2007 Aug;7(16):2856-69. Review.

PMID:
17703505
7.

Computational analysis of miRNA targets in plants: current status and challenges.

Dai X, Zhuang Z, Zhao PX.

Brief Bioinform. 2011 Mar;12(2):115-21. doi: 10.1093/bib/bbq065. Epub 2010 Sep 21. Review.

PMID:
20858738
8.

Comparative co-expression analysis in plant biology.

Movahedi S, Van Bel M, Heyndrickx KS, Vandepoele K.

Plant Cell Environ. 2012 Oct;35(10):1787-98. doi: 10.1111/j.1365-3040.2012.02517.x. Epub 2012 May 10. Review.

9.

Annotation of gene function in citrus using gene expression information and co-expression networks.

Wong DC, Sweetman C, Ford CM.

BMC Plant Biol. 2014 Jul 15;14:186. doi: 10.1186/1471-2229-14-186.

10.

Network analysis for gene discovery in plant-specialized metabolism.

Higashi Y, Saito K.

Plant Cell Environ. 2013 Sep;36(9):1597-606. doi: 10.1111/pce.12069. Epub 2013 Feb 21. Review.

11.

A review on the computational approaches for gene regulatory network construction.

Chai LE, Loh SK, Low ST, Mohamad MS, Deris S, Zakaria Z.

Comput Biol Med. 2014 May;48:55-65. doi: 10.1016/j.compbiomed.2014.02.011. Epub 2014 Feb 24. Review.

PMID:
24637147
12.

Co-expression tools for plant biology: opportunities for hypothesis generation and caveats.

Usadel B, Obayashi T, Mutwil M, Giorgi FM, Bassel GW, Tanimoto M, Chow A, Steinhauser D, Persson S, Provart NJ.

Plant Cell Environ. 2009 Dec;32(12):1633-51. doi: 10.1111/j.1365-3040.2009.02040.x. Epub 2009 Aug 27. Review.

13.

Toward microRNA-mediated gene regulatory networks in plants.

Meng Y, Shao C, Chen M.

Brief Bioinform. 2011 Nov;12(6):645-59. doi: 10.1093/bib/bbq091. Epub 2011 Jan 23.

PMID:
21262742
14.

IRIS: a method for reverse engineering of regulatory relations in gene networks.

Morganella S, Zoppoli P, Ceccarelli M.

BMC Bioinformatics. 2009 Dec 23;10:444. doi: 10.1186/1471-2105-10-444.

15.

Module network inference from a cancer gene expression data set identifies microRNA regulated modules.

Bonnet E, Tatari M, Joshi A, Michoel T, Marchal K, Berx G, Van de Peer Y.

PLoS One. 2010 Apr 14;5(4):e10162. doi: 10.1371/journal.pone.0010162.

16.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

Wong DC, Sweetman C, Drew DP, Ford CM.

BMC Genomics. 2013 Dec 16;14:882. doi: 10.1186/1471-2164-14-882.

17.

Cross-platform microarray data normalisation for regulatory network inference.

Sîrbu A, Ruskin HJ, Crane M.

PLoS One. 2010 Nov 12;5(11):e13822. doi: 10.1371/journal.pone.0013822.

18.

Towards understanding how molecular networks evolve in plants.

Chae L, Lee I, Shin J, Rhee SY.

Curr Opin Plant Biol. 2012 Apr;15(2):177-84. doi: 10.1016/j.pbi.2012.01.006. Epub 2012 Jan 24. Review.

PMID:
22280840
19.

GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop.

Montojo J, Zuberi K, Rodriguez H, Kazi F, Wright G, Donaldson SL, Morris Q, Bader GD.

Bioinformatics. 2010 Nov 15;26(22):2927-8. doi: 10.1093/bioinformatics/btq562. Epub 2010 Oct 5.

20.

VAN: an R package for identifying biologically perturbed networks via differential variability analysis.

Jayaswal V, Schramm SJ, Mann GJ, Wilkins MR, Yang YH.

BMC Res Notes. 2013 Oct 25;6:430. doi: 10.1186/1756-0500-6-430.

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