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Items: 1 to 20 of 26

1.

A comprehensive review of web-based resources of non-coding RNAs for plant science research.

Liao P, Li S, Cui X, Zheng Y.

Int J Biol Sci. 2018 May 22;14(8):819-832. doi: 10.7150/ijbs.24593. eCollection 2018. Review.

2.

SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs.

Shi J, Ko EA, Sanders KM, Chen Q, Zhou T.

Genomics Proteomics Bioinformatics. 2018 Apr;16(2):144-151. doi: 10.1016/j.gpb.2018.04.004. Epub 2018 May 3.

3.

The discovery potential of RNA processing profiles.

Pagès A, Dotu I, Pallarès-Albanell J, Martí E, Guigó R, Eyras E.

Nucleic Acids Res. 2018 Feb 16;46(3):e15. doi: 10.1093/nar/gkx1115.

4.

Nuclear export factor 3 regulates localization of small nucleolar RNAs.

Li MW, Sletten AC, Lee J, Pyles KD, Matkovich SJ, Ory DS, Schaffer JE.

J Biol Chem. 2017 Dec 8;292(49):20228-20239. doi: 10.1074/jbc.M117.818146. Epub 2017 Oct 11.

5.

Circulating microRNAs and Bioinformatics Tools to Discover Novel Diagnostic Biomarkers of Pediatric Diseases.

Baldassarre A, Felli C, Prantera G, Masotti A.

Genes (Basel). 2017 Sep 19;8(9). pii: E234. doi: 10.3390/genes8090234. Review.

6.

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench.

Beckers M, Mohorianu I, Stocks M, Applegate C, Dalmay T, Moulton V.

RNA. 2017 Jun;23(6):823-835. doi: 10.1261/rna.059360.116. Epub 2017 Mar 13.

7.

Nutrition, microRNAs, and Human Health.

Cui J, Zhou B, Ross SA, Zempleni J.

Adv Nutr. 2017 Jan 17;8(1):105-112. doi: 10.3945/an.116.013839. Print 2017 Jan. Review.

8.

miRDis: a Web tool for endogenous and exogenous microRNA discovery based on deep-sequencing data analysis.

Zhang H, Vieira Resende E Silva B, Cui J.

Brief Bioinform. 2018 May 1;19(3):415-424. doi: 10.1093/bib/bbw140.

9.

Integrating Epigenomics into the Understanding of Biomedical Insight.

Han Y, He X.

Bioinform Biol Insights. 2016 Dec 4;10:267-289. eCollection 2016. Review.

10.

Identification of urinary exosomal noncoding RNAs as novel biomarkers in chronic kidney disease.

Khurana R, Ranches G, Schafferer S, Lukasser M, Rudnicki M, Mayer G, Hüttenhofer A.

RNA. 2017 Feb;23(2):142-152. doi: 10.1261/rna.058834.116. Epub 2016 Nov 21.

11.

Non-coding RNA profiling of the developing murine lens.

Khan SY, Hackett SF, Riazuddin SA.

Exp Eye Res. 2016 Apr;145:347-351. doi: 10.1016/j.exer.2016.01.010. Epub 2016 Jan 22.

12.

miFRame: analysis and visualization of miRNA sequencing data in neurological disorders.

Backes C, Haas J, Leidinger P, Frese K, Großmann T, Ruprecht K, Meder B, Meese E, Keller A.

J Transl Med. 2015 Jul 14;13:224. doi: 10.1186/s12967-015-0594-x.

13.

Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques.

Veneziano D, Nigita G, Ferro A.

Front Bioeng Biotechnol. 2015 Jun 3;3:77. doi: 10.3389/fbioe.2015.00077. eCollection 2015. Review.

14.

sRNAtoolbox: an integrated collection of small RNA research tools.

Rueda A, Barturen G, Lebrón R, Gómez-Martín C, Alganza Á, Oliver JL, Hackenberg M.

Nucleic Acids Res. 2015 Jul 1;43(W1):W467-73. doi: 10.1093/nar/gkv555. Epub 2015 May 27.

15.

plantDARIO: web based quantitative and qualitative analysis of small RNA-seq data in plants.

Patra D, Fasold M, Langenberger D, Steger G, Grosse I, Stadler PF.

Front Plant Sci. 2014 Dec 23;5:708. doi: 10.3389/fpls.2014.00708. eCollection 2014.

16.

Small non-coding RNA profiling and the role of piRNA pathway genes in the protection of chicken primordial germ cells.

Rengaraj D, Lee SI, Park TS, Lee HJ, Kim YM, Sohn YA, Jung M, Noh SJ, Jung H, Han JY.

BMC Genomics. 2014 Sep 4;15:757. doi: 10.1186/1471-2164-15-757.

17.

Search for microRNAs expressed by intracellular bacterial pathogens in infected mammalian cells.

Furuse Y, Finethy R, Saka HA, Xet-Mull AM, Sisk DM, Smith KL, Lee S, Coers J, Valdivia RH, Tobin DM, Cullen BR.

PLoS One. 2014 Sep 3;9(9):e106434. doi: 10.1371/journal.pone.0106434. eCollection 2014.

18.

BlockClust: efficient clustering and classification of non-coding RNAs from short read RNA-seq profiles.

Videm P, Rose D, Costa F, Backofen R.

Bioinformatics. 2014 Jun 15;30(12):i274-82. doi: 10.1093/bioinformatics/btu270.

19.

Persistently adenovirus-infected lymphoid cells express microRNAs derived from the viral VAI and especially VAII RNA.

Furuse Y, Ornelles DA, Cullen BR.

Virology. 2013 Dec;447(1-2):140-5. doi: 10.1016/j.virol.2013.08.024. Epub 2013 Sep 26.

20.

Using machine learning and high-throughput RNA sequencing to classify the precursors of small non-coding RNAs.

Ryvkin P, Leung YY, Ungar LH, Gregory BD, Wang LS.

Methods. 2014 May 1;67(1):28-35. doi: 10.1016/j.ymeth.2013.10.002. Epub 2013 Oct 18.

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