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Items: 1 to 20 of 143

1.

Utilizing RNA-Seq data for de novo coexpression network inference.

Iancu OD, Kawane S, Bottomly D, Searles R, Hitzemann R, McWeeney S.

Bioinformatics. 2012 Jun 15;28(12):1592-7. doi: 10.1093/bioinformatics/bts245. Epub 2012 May 3.

2.

Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana.

Giorgi FM, Del Fabbro C, Licausi F.

Bioinformatics. 2013 Mar 15;29(6):717-24. doi: 10.1093/bioinformatics/btt053. Epub 2013 Feb 1.

3.

Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrays.

Bottomly D, Walter NA, Hunter JE, Darakjian P, Kawane S, Buck KJ, Searles RP, Mooney M, McWeeney SK, Hitzemann R.

PLoS One. 2011 Mar 24;6(3):e17820. doi: 10.1371/journal.pone.0017820.

4.

Coexpression and cosplicing network approaches for the study of mammalian brain transcriptomes.

Iancu OD, Colville A, Darakjian P, Hitzemann R.

Int Rev Neurobiol. 2014;116:73-93. doi: 10.1016/B978-0-12-801105-8.00004-7. Review.

PMID:
25172472
5.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

Zhu M, Dahmen JL, Stacey G, Cheng J.

BMC Bioinformatics. 2013 Sep 22;14:278. doi: 10.1186/1471-2105-14-278.

6.

Maize gene atlas developed by RNA sequencing and comparative evaluation of transcriptomes based on RNA sequencing and microarrays.

Sekhon RS, Briskine R, Hirsch CN, Myers CL, Springer NM, Buell CR, de Leon N, Kaeppler SM.

PLoS One. 2013 Apr 23;8(4):e61005. doi: 10.1371/journal.pone.0061005. Print 2013. Erratum in: PLoS One. 2014;9(1). doi:10.1371/annotation/0444d495-9231-4097-abe0-4750b9045971.

7.

RNA-Seq vs dual- and single-channel microarray data: sensitivity analysis for differential expression and clustering.

Sîrbu A, Kerr G, Crane M, Ruskin HJ.

PLoS One. 2012;7(12):e50986. doi: 10.1371/journal.pone.0050986. Epub 2012 Dec 10.

8.

Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.

Miller JA, Menon V, Goldy J, Kaykas A, Lee CK, Smith KA, Shen EH, Phillips JW, Lein ES, Hawrylycz MJ.

BMC Genomics. 2014 Feb 24;15:154. doi: 10.1186/1471-2164-15-154.

9.

Genes, behavior and next-generation RNA sequencing.

Hitzemann R, Bottomly D, Darakjian P, Walter N, Iancu O, Searles R, Wilmot B, McWeeney S.

Genes Brain Behav. 2013 Feb;12(1):1-12. doi: 10.1111/gbb.12007. Epub 2012 Dec 28. Review.

10.

Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments.

Black MB, Parks BB, Pluta L, Chu TM, Allen BC, Wolfinger RD, Thomas RS.

Toxicol Sci. 2014 Feb;137(2):385-403. doi: 10.1093/toxsci/kft249. Epub 2013 Nov 5.

11.

RNA-Seq versus oligonucleotide array assessment of dose-dependent TCDD-elicited hepatic gene expression in mice.

Nault R, Fader KA, Zacharewski T.

BMC Genomics. 2015 May 10;16:373. doi: 10.1186/s12864-015-1527-z.

12.

Comparing next-generation sequencing and microarray technologies in a toxicological study of the effects of aristolochic acid on rat kidneys.

Su Z, Li Z, Chen T, Li QZ, Fang H, Ding D, Ge W, Ning B, Hong H, Perkins RG, Tong W, Shi L.

Chem Res Toxicol. 2011 Sep 19;24(9):1486-93. doi: 10.1021/tx200103b. Epub 2011 Aug 23.

PMID:
21834575
13.

RNA-Seq Atlas--a reference database for gene expression profiling in normal tissue by next-generation sequencing.

Krupp M, Marquardt JU, Sahin U, Galle PR, Castle J, Teufel A.

Bioinformatics. 2012 Apr 15;28(8):1184-5. doi: 10.1093/bioinformatics/bts084. Epub 2012 Feb 17.

14.

Parallel comparison of Illumina RNA-Seq and Affymetrix microarray platforms on transcriptomic profiles generated from 5-aza-deoxy-cytidine treated HT-29 colon cancer cells and simulated datasets.

Xu X, Zhang Y, Williams J, Antoniou E, McCombie WR, Wu S, Zhu W, Davidson NO, Denoya P, Li E.

BMC Bioinformatics. 2013;14 Suppl 9:S1. doi: 10.1186/1471-2105-14-S9-S1. Epub 2013 Jun 28.

15.

Guidance for RNA-seq co-expression network construction and analysis: safety in numbers.

Ballouz S, Verleyen W, Gillis J.

Bioinformatics. 2015 Jul 1;31(13):2123-30. doi: 10.1093/bioinformatics/btv118. Epub 2015 Feb 24.

16.

Exploring the gonad transcriptome of two extreme male pigs with RNA-seq.

Esteve-Codina A, Kofler R, Palmieri N, Bussotti G, Notredame C, Pérez-Enciso M.

BMC Genomics. 2011 Nov 8;12:552. doi: 10.1186/1471-2164-12-552.

17.

Weighted gene coexpression network analysis strategies applied to mouse weight.

Fuller TF, Ghazalpour A, Aten JE, Drake TA, Lusis AJ, Horvath S.

Mamm Genome. 2007 Jul;18(6-7):463-72. Epub 2007 Aug 1.

18.

Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells.

Zhao S, Fung-Leung WP, Bittner A, Ngo K, Liu X.

PLoS One. 2014 Jan 16;9(1):e78644. doi: 10.1371/journal.pone.0078644. eCollection 2014.

19.

Introduction to sequencing the brain transcriptome.

Hitzemann R, Darakjian P, Walter N, Iancu OD, Searles R, McWeeney S.

Int Rev Neurobiol. 2014;116:1-19. doi: 10.1016/B978-0-12-801105-8.00001-1. Review.

20.

Gene coexpression network analysis as a source of functional annotation for rice genes.

Childs KL, Davidson RM, Buell CR.

PLoS One. 2011;6(7):e22196. doi: 10.1371/journal.pone.0022196. Epub 2011 Jul 22.

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