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Results: 1 to 20 of 390

Similar articles for PubMed (Select 21455293)

1.

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.

2.

High throughput sequencing in mice: a platform comparison identifies a preponderance of cryptic SNPs.

Walter NA, Bottomly D, Laderas T, Mooney MA, Darakjian P, Searles RP, Harrington CA, McWeeney SK, Hitzemann R, Buck KJ.

BMC Genomics. 2009 Aug 17;10:379. doi: 10.1186/1471-2164-10-379.

3.

Next-generation sequencing facilitates quantitative analysis of wild-type and Nrl(-/-) retinal transcriptomes.

Brooks MJ, Rajasimha HK, Roger JE, Swaroop A.

Mol Vis. 2011;17:3034-54. Epub 2011 Nov 23.

4.

Gene expression profiling in the striatum of inbred mouse strains with distinct opioid-related phenotypes.

Korostynski M, Kaminska-Chowaniec D, Piechota M, Przewlocki R.

BMC Genomics. 2006 Jun 13;7:146.

5.

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
6.

A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae.

Nookaew I, Papini M, Pornputtapong N, Scalcinati G, Fagerberg L, Uhlén M, Nielsen J.

Nucleic Acids Res. 2012 Nov 1;40(20):10084-97. doi: 10.1093/nar/gks804. Epub 2012 Sep 10.

7.

A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling.

Bradford JR, Hey Y, Yates T, Li Y, Pepper SD, Miller CJ.

BMC Genomics. 2010 May 5;11:282. doi: 10.1186/1471-2164-11-282.

8.

Exon and junction microarrays detect widespread mouse strain- and sex-bias expression differences.

Su WL, Modrek B, GuhaThakurta D, Edwards S, Shah JK, Kulkarni AV, Russell A, Schadt EE, Johnson JM, Castle JC.

BMC Genomics. 2008 Jun 4;9:273. doi: 10.1186/1471-2164-9-273.

9.

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.

10.

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.

11.

A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease.

Raghavachari N, Barb J, Yang Y, Liu P, Woodhouse K, Levy D, O'Donnell CJ, Munson PJ, Kato GJ.

BMC Med Genomics. 2012 Jun 29;5:28. doi: 10.1186/1755-8794-5-28.

12.

High-throughput RNA-seq for allelic or locus-specific expression analysis in Arabidopsis-related species, hybrids, and allotetraploids.

Ng DW, Shi X, Nah G, Chen ZJ.

Methods Mol Biol. 2014;1112:33-48. doi: 10.1007/978-1-62703-773-0_3.

PMID:
24478006
13.

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.

14.

A comparison of RNA-Seq and high-density exon array for detecting differential gene expression between closely related species.

Liu S, Lin L, Jiang P, Wang D, Xing Y.

Nucleic Acids Res. 2011 Jan;39(2):578-88. doi: 10.1093/nar/gkq817. Epub 2010 Sep 22.

15.

Global expression profiles from C57BL/6J and DBA/2J mouse lungs to determine aging-related genes.

Misra V, Lee H, Singh A, Huang K, Thimmulappa RK, Mitzner W, Biswal S, Tankersley CG.

Physiol Genomics. 2007 Nov 14;31(3):429-40. Epub 2007 Aug 28.

16.

RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays.

Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y.

Genome Res. 2008 Sep;18(9):1509-17. doi: 10.1101/gr.079558.108. Epub 2008 Jun 11.

17.

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.

18.

Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing.

Mane SP, Evans C, Cooper KL, Crasta OR, Folkerts O, Hutchison SK, Harkins TT, Thierry-Mieg D, Thierry-Mieg J, Jensen RV.

BMC Genomics. 2009 Jun 12;10:264. doi: 10.1186/1471-2164-10-264.

19.

EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics.

Rallapalli G, Kemen EM, Robert-Seilaniantz A, Segonzac C, Etherington GJ, Sohn KH, MacLean D, Jones JD.

BMC Genomics. 2014 May 6;15:341. doi: 10.1186/1471-2164-15-341.

20.

Comparative transcriptome analysis of epithelial and fiber cells in newborn mouse lenses with RNA sequencing.

Hoang TV, Kumar PK, Sutharzan S, Tsonis PA, Liang C, Robinson ML.

Mol Vis. 2014 Nov 4;20:1491-517. eCollection 2014.

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