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Items: 1 to 20 of 101

1.

anamiR: integrated analysis of MicroRNA and gene expression profiling.

Wang TT, Lee CY, Lai LC, Tsai MH, Lu TP, Chuang EY.

BMC Bioinformatics. 2019 May 14;20(1):239. doi: 10.1186/s12859-019-2870-x.

2.

iGC-an integrated analysis package of gene expression and copy number alteration.

Lai YP, Wang LB, Wang WA, Lai LC, Tsai MH, Lu TP, Chuang EY.

BMC Bioinformatics. 2017 Jan 14;18(1):35. doi: 10.1186/s12859-016-1438-2.

3.

mAPKL: R/ Bioconductor package for detecting gene exemplars and revealing their characteristics.

Sakellariou A, Spyrou G.

BMC Bioinformatics. 2015 Sep 15;16:291. doi: 10.1186/s12859-015-0719-5.

4.
5.

Trendy: segmented regression analysis of expression dynamics in high-throughput ordered profiling experiments.

Bacher R, Leng N, Chu LF, Ni Z, Thomson JA, Kendziorski C, Stewart R.

BMC Bioinformatics. 2018 Oct 16;19(1):380. doi: 10.1186/s12859-018-2405-x.

6.

A bioinformatics tool for linking gene expression profiling results with public databases of microRNA target predictions.

Creighton CJ, Nagaraja AK, Hanash SM, Matzuk MM, Gunaratne PH.

RNA. 2008 Nov;14(11):2290-6. doi: 10.1261/rna.1188208. Epub 2008 Sep 23.

7.

Microarray-Based MicroRNA Expression Data Analysis with Bioconductor.

Mastriani E, Zhai R, Zhu S.

Methods Mol Biol. 2018;1751:127-138. doi: 10.1007/978-1-4939-7710-9_9.

PMID:
29508294
8.

MiRSEA: Discovering the pathways regulated by dysfunctional MicroRNAs.

Han J, Liu S, Zhang Y, Xu Y, Jiang Y, Zhang C, Li C, Li X.

Oncotarget. 2016 Aug 23;7(34):55012-55025. doi: 10.18632/oncotarget.10839.

9.

clusterProfiler: an R package for comparing biological themes among gene clusters.

Yu G, Wang LG, Han Y, He QY.

OMICS. 2012 May;16(5):284-7. doi: 10.1089/omi.2011.0118. Epub 2012 Mar 28.

10.

GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases.

Zhu LJ, Lawrence M, Gupta A, Pagès H, Kucukural A, Garber M, Wolfe SA.

BMC Genomics. 2017 May 15;18(1):379. doi: 10.1186/s12864-017-3746-y.

11.

SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq data integrating differential expression and splicing.

Wang X, Cairns MJ.

Bioinformatics. 2014 Jun 15;30(12):1777-9. doi: 10.1093/bioinformatics/btu090. Epub 2014 Feb 17.

PMID:
24535097
12.

MiRE: a graphical R package for microRNA-related analysis.

Yan XQ, Tu K, Xie L, Li YX, Yin B, Gong YH, Yuan JG, Qiang BQ, Peng XZ.

Chin Med Sci J. 2008 Dec;23(4):202-4.

PMID:
19180879
13.

GeneExpressionSignature: an R package for discovering functional connections using gene expression signatures.

Li F, Cao Y, Han L, Cui X, Xie D, Wang S, Bo X.

OMICS. 2013 Feb;17(2):116-8. doi: 10.1089/omi.2012.0087.

PMID:
23374109
14.

Large-scale integration of MicroRNA and gene expression data for identification of enriched microRNA-mRNA associations in biological systems.

Gunaratne PH, Creighton CJ, Watson M, Tennakoon JB.

Methods Mol Biol. 2010;667:297-315. doi: 10.1007/978-1-60761-811-9_20.

PMID:
20827542
15.

Integrated microRNA and mRNA expression profiling in a rat colon carcinogenesis model: effect of a chemo-protective diet.

Shah MS, Schwartz SL, Zhao C, Davidson LA, Zhou B, Lupton JR, Ivanov I, Chapkin RS.

Physiol Genomics. 2011 May 1;43(10):640-54. doi: 10.1152/physiolgenomics.00213.2010. Epub 2011 Mar 15.

16.

Integrated analyses to reconstruct microRNA-mediated regulatory networks in mouse liver using high-throughput profiling.

Hsu SD, Huang HY, Chou CH, Sun YM, Hsu MT, Tsou AP.

BMC Genomics. 2015;16 Suppl 2:S12. doi: 10.1186/1471-2164-16-S2-S12. Epub 2015 Jan 21.

17.

Analysis of microarray-identified genes and microRNAs associated with drug resistance in ovarian cancer.

Zou J, Yin F, Wang Q, Zhang W, Li L.

Int J Clin Exp Pathol. 2015 Jun 1;8(6):6847-58. eCollection 2015.

18.

GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, miRNA and mRNA data in GDC.

Li R, Qu H, Wang S, Wei J, Zhang L, Ma R, Lu J, Zhu J, Zhong WD, Jia Z.

Bioinformatics. 2018 Jul 15;34(14):2515-2517. doi: 10.1093/bioinformatics/bty124.

PMID:
29509844
19.

compcodeR--an R package for benchmarking differential expression methods for RNA-seq data.

Soneson C.

Bioinformatics. 2014 Sep 1;30(17):2517-8. doi: 10.1093/bioinformatics/btu324. Epub 2014 May 9.

PMID:
24813215
20.

SpeCond: a method to detect condition-specific gene expression.

Cavalli FM, Bourgon R, Vaquerizas JM, Luscombe NM.

Genome Biol. 2011 Oct 18;12(10):R101. doi: 10.1186/gb-2011-12-10-r101. Erratum in: Genome Biol. 2011;12(12):413. Huber, Wolfgang [removed].

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