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Items: 16

1.

Development of species specific putative miRNA and its target prediction tool in wheat (Triticum aestivum L.).

Jaiswal S, Iquebal MA, Arora V, Sheoran S, Sharma P, Angadi UB, Dahiya V, Singh R, Tiwari R, Singh GP, Rai A, Kumar D.

Sci Rep. 2019 Mar 7;9(1):3790. doi: 10.1038/s41598-019-40333-y.

2.

Adaboost-SVM-based probability algorithm for the prediction of all mature miRNA sites based on structured-sequence features.

Wang Y, Ru J, Jiang Y, Zhang J.

Sci Rep. 2019 Feb 6;9(1):1521. doi: 10.1038/s41598-018-38048-7.

3.

StarSeeker: an automated tool for mature duplex microRNA sequence identification based on secondary structure modeling of precursor molecule.

Natsidis P, Kappas I, Karlowski WM.

J Biol Res (Thessalon). 2018 Jun 15;25:11. doi: 10.1186/s40709-018-0081-7. eCollection 2018 Dec.

4.

Transcriptome-Wide Annotation of m5C RNA Modifications Using Machine Learning.

Song J, Zhai J, Bian E, Song Y, Yu J, Ma C.

Front Plant Sci. 2018 Apr 18;9:519. doi: 10.3389/fpls.2018.00519. eCollection 2018. Erratum in: Front Plant Sci. 2018 Nov 30;9:1762.

5.

Comparing miRNA structure of mirtrons and non-mirtrons.

Titov II, Vorozheykin PS.

BMC Genomics. 2018 Feb 9;19(Suppl 3):114. doi: 10.1186/s12864-018-4473-8.

6.

Identification and Characterization of Microsatellite Loci in Maqui (Aristotelia chilensis [Molina] Stunz) Using Next-Generation Sequencing (NGS).

Bastías A, Correa F, Rojas P, Almada R, Muñoz C, Sagredo B.

PLoS One. 2016 Jul 26;11(7):e0159825. doi: 10.1371/journal.pone.0159825. eCollection 2016.

7.

Improving classification of mature microRNA by solving class imbalance problem.

Wang Y, Li X, Tao B.

Sci Rep. 2016 May 16;6:25941. doi: 10.1038/srep25941.

8.

miRNA Digger: a comprehensive pipeline for genome-wide novel miRNA mining.

Yu L, Shao C, Ye X, Meng Y, Zhou Y, Chen M.

Sci Rep. 2016 Jan 6;6:18901. doi: 10.1038/srep18901.

9.

MatPred: Computational Identification of Mature MicroRNAs within Novel Pre-MicroRNAs.

Li J, Wang Y, Wang L, Feng W, Luan K, Dai X, Xu C, Meng X, Zhang Q, Liang H.

Biomed Res Int. 2015;2015:546763. doi: 10.1155/2015/546763. Epub 2015 Nov 23.

10.

Improved Pre-miRNA Classification by Reducing the Effect of Class Imbalance.

Zhong Y, Xuan P, Han K, Zhang W, Li J.

Biomed Res Int. 2015;2015:960108. doi: 10.1155/2015/960108. Epub 2015 Nov 10.

11.

miRLocator: Machine Learning-Based Prediction of Mature MicroRNAs within Plant Pre-miRNA Sequences.

Cui H, Zhai J, Ma C.

PLoS One. 2015 Nov 11;10(11):e0142753. doi: 10.1371/journal.pone.0142753. eCollection 2015.

12.

Dietary MicroRNA Database (DMD): An Archive Database and Analytic Tool for Food-Borne microRNAs.

Chiang K, Shu J, Zempleni J, Cui J.

PLoS One. 2015 Jun 1;10(6):e0128089. doi: 10.1371/journal.pone.0128089. eCollection 2015.

13.

MiRduplexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Methodology.

Karathanasis N, Tsamardinos I, Poirazi P.

PLoS One. 2015 May 11;10(5):e0126151. doi: 10.1371/journal.pone.0126151. eCollection 2015.

14.

Secondary structural entropy in RNA switch (Riboswitch) identification.

Manzourolajdad A, Arnold J.

BMC Bioinformatics. 2015 Apr 28;16:133. doi: 10.1186/s12859-015-0523-2.

15.

An integrative approach to identify hexaploid wheat miRNAome associated with development and tolerance to abiotic stress.

Agharbaoui Z, Leclercq M, Remita MA, Badawi MA, Lord E, Houde M, Danyluk J, Diallo AB, Sarhan F.

BMC Genomics. 2015 Apr 24;16:339. doi: 10.1186/s12864-015-1490-8.

16.

Identification of differentially expressed microRNAs in Culex pipiens and their potential roles in pyrethroid resistance.

Hong S, Guo Q, Wang W, Hu S, Fang F, Lv Y, Yu J, Zou F, Lei Z, Ma K, Ma L, Zhou D, Sun Y, Zhang D, Shen B, Zhu C.

Insect Biochem Mol Biol. 2014 Dec;55:39-50. doi: 10.1016/j.ibmb.2014.10.007. Epub 2014 Nov 5.

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