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Items: 1 to 20 of 61

1.

Improved Pre-miRNAs Identification Through Mutual Information of Pre-miRNA Sequences and Structures.

Fu X, Zhu W, Cai L, Liao B, Peng L, Chen Y, Yang J.

Front Genet. 2019 Feb 25;10:119. doi: 10.3389/fgene.2019.00119. eCollection 2019.

2.

Identification of pre-microRNAs by characterizing their sequence order evolution information and secondary structure graphs.

Ma Y, Yu Z, Han G, Li J, Anh V.

BMC Bioinformatics. 2018 Dec 31;19(Suppl 19):521. doi: 10.1186/s12859-018-2518-2.

3.

Distinguishing mirtrons from canonical miRNAs with data exploration and machine learning methods.

Rorbach G, Unold O, Konopka BM.

Sci Rep. 2018 May 15;8(1):7560. doi: 10.1038/s41598-018-25578-3.

4.

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

Fehlmann T, Backes C, Kahraman M, Haas J, Ludwig N, Posch AE, Würstle ML, Hübenthal M, Franke A, Meder B, Meese E, Keller A.

Nucleic Acids Res. 2017 Sep 6;45(15):8731-8744. doi: 10.1093/nar/gkx595.

5.

On the performance of pre-microRNA detection algorithms.

Saçar Demirci MD, Baumbach J, Allmer J.

Nat Commun. 2017 Aug 24;8(1):330. doi: 10.1038/s41467-017-00403-z.

6.

An improved method for identification of small non-coding RNAs in bacteria using support vector machine.

Barman RK, Mukhopadhyay A, Das S.

Sci Rep. 2017 Apr 6;7:46070. doi: 10.1038/srep46070.

7.

Delineating the impact of machine learning elements in pre-microRNA detection.

Saçar Demirci MD, Allmer J.

PeerJ. 2017 Mar 29;5:e3131. doi: 10.7717/peerj.3131. eCollection 2017.

8.
9.

MicroRNA categorization using sequence motifs and k-mers.

Yousef M, Khalifa W, Acar İE, Allmer J.

BMC Bioinformatics. 2017 Mar 14;18(1):170. doi: 10.1186/s12859-017-1584-1.

10.

Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

Marques YB, de Paiva Oliveira A, Ribeiro Vasconcelos AT, Cerqueira FR.

BMC Bioinformatics. 2016 Dec 15;17(Suppl 18):474. doi: 10.1186/s12859-016-1343-8. Erratum in: BMC Bioinformatics. 2017 Feb 17;18(1):113.

11.

A Review of Computational Methods for Finding Non-Coding RNA Genes.

Abbas Q, Raza SM, Biyabani AA, Jaffar MA.

Genes (Basel). 2016 Dec 3;7(12). pii: E113. Review.

12.

Automatic learning of pre-miRNAs from different species.

O N Lopes Id, Schliep A, de L F de Carvalho AP.

BMC Bioinformatics. 2016 May 28;17(1):224. doi: 10.1186/s12859-016-1036-3.

13.

Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values.

Razzaghi T, Roderick O, Safro I, Marko N.

PLoS One. 2016 May 19;11(5):e0155119. doi: 10.1371/journal.pone.0155119. eCollection 2016.

14.

Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants.

Yousef M, Saçar Demirci MD, Khalifa W, Allmer J.

Adv Bioinformatics. 2016;2016:5670851. doi: 10.1155/2016/5670851. Epub 2016 Apr 12.

15.

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.

16.

IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association.

Peguero-Sanchez E, Pardo-Lopez L, Merino E.

BMC Genomics. 2015 Dec 15;16:1059. doi: 10.1186/s12864-015-2266-x.

17.

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.

18.

Computational Characterization of Exogenous MicroRNAs that Can Be Transferred into Human Circulation.

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

PLoS One. 2015 Nov 3;10(11):e0140587. doi: 10.1371/journal.pone.0140587. eCollection 2015.

19.

A framework for improving microRNA prediction in non-human genomes.

Peace RJ, Biggar KK, Storey KB, Green JR.

Nucleic Acids Res. 2015 Nov 16;43(20):e138. doi: 10.1093/nar/gkv698. Epub 2015 Jul 10.

20.

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.

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