438 related articles for article (PubMed ID: 30635896)
1. Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome.
Monga I; Kumar M
Methods Mol Biol; 2019; 1912():215-250. PubMed ID: 30635896
[TBL] [Abstract][Full Text] [Related]
2. Computational Prediction of Functional MicroRNA-mRNA Interactions.
Saçar Demirci MD; Yousef M; Allmer J
Methods Mol Biol; 2019; 1912():175-196. PubMed ID: 30635894
[TBL] [Abstract][Full Text] [Related]
3. BioVLAB-MMIA-NGS: microRNA-mRNA integrated analysis using high-throughput sequencing data.
Chae H; Rhee S; Nephew KP; Kim S
Bioinformatics; 2015 Jan; 31(2):265-7. PubMed ID: 25270639
[TBL] [Abstract][Full Text] [Related]
4. Comprehensive analysis of small RNA-seq data reveals that combination of miRNA with its isomiRs increase the accuracy of target prediction in Arabidopsis thaliana.
Ahmed F; Senthil-Kumar M; Lee S; Dai X; Mysore KS; Zhao PX
RNA Biol; 2014; 11(11):1414-29. PubMed ID: 25629686
[TBL] [Abstract][Full Text] [Related]
5. Computational and Experimental Identification of Tissue-Specific MicroRNA Targets.
Amirkhah R; Meshkin HN; Farazmand A; Rasko JEJ; Schmitz U
Methods Mol Biol; 2017; 1580():127-147. PubMed ID: 28439832
[TBL] [Abstract][Full Text] [Related]
6. Computational Approaches and Related Tools to Identify MicroRNAs in a Species: A Bird's Eye View.
Rajendiran A; Chatterjee A; Pan A
Interdiscip Sci; 2018 Sep; 10(3):616-635. PubMed ID: 28361256
[TBL] [Abstract][Full Text] [Related]
7. Identification and validation of plant miRNA from NGS data-an experimental approach.
Devi K; Dey KK; Singh S; Mishra SK; Modi MK; Sen P
Brief Funct Genomics; 2019 Feb; 18(1):13-22. PubMed ID: 30335137
[TBL] [Abstract][Full Text] [Related]
8. Next-generation sequencing identifies the natural killer cell microRNA transcriptome.
Fehniger TA; Wylie T; Germino E; Leong JW; Magrini VJ; Koul S; Keppel CR; Schneider SE; Koboldt DC; Sullivan RP; Heinz ME; Crosby SD; Nagarajan R; Ramsingh G; Link DC; Ley TJ; Mardis ER
Genome Res; 2010 Nov; 20(11):1590-604. PubMed ID: 20935160
[TBL] [Abstract][Full Text] [Related]
9. A Distributed Classifier for MicroRNA Target Prediction with Validation Through TCGA Expression Data.
Ghoshal A; Zhang J; Roth MA; Xia KM; Grama AY; Chaterji S
IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(4):1037-1051. PubMed ID: 29993641
[TBL] [Abstract][Full Text] [Related]
10. Bioinformatic Analysis of MicroRNA Sequencing Data.
Fu X; Dong D
Methods Mol Biol; 2018; 1751():109-125. PubMed ID: 29508293
[TBL] [Abstract][Full Text] [Related]
11. microRPM: a microRNA prediction model based only on plant small RNA sequencing data.
Tseng KC; Chiang-Hsieh YF; Pai H; Chow CN; Lee SC; Zheng HQ; Kuo PL; Li GZ; Hung YC; Lin NS; Chang WC
Bioinformatics; 2018 Apr; 34(7):1108-1115. PubMed ID: 29136092
[TBL] [Abstract][Full Text] [Related]
12. MicroRNA Expression Analysis: Next-Generation Sequencing.
Liu P
Methods Mol Biol; 2018; 1783():171-183. PubMed ID: 29767362
[TBL] [Abstract][Full Text] [Related]
13. Accurate prediction of human miRNA targets via graph modeling of the miRNA-target duplex.
Mohebbi M; Ding L; Malmberg RL; Momany C; Rasheed K; Cai L
J Bioinform Comput Biol; 2018 Aug; 16(4):1850013. PubMed ID: 30012015
[TBL] [Abstract][Full Text] [Related]
14. Identification of Taxus microRNAs and their targets with high-throughput sequencing and degradome analysis.
Hao DC; Yang L; Xiao PG; Liu M
Physiol Plant; 2012 Dec; 146(4):388-403. PubMed ID: 22708792
[TBL] [Abstract][Full Text] [Related]
15. 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; 45(15):8731-8744. PubMed ID: 28911107
[TBL] [Abstract][Full Text] [Related]
16. Machine Learning Based Methods and Best Practices of microRNA-Target Prediction and Validation.
Nath N; Simm S
Adv Exp Med Biol; 2022; 1385():109-131. PubMed ID: 36352212
[TBL] [Abstract][Full Text] [Related]
17. miRNAs target databases: developmental methods and target identification techniques with functional annotations.
Singh NK
Cell Mol Life Sci; 2017 Jun; 74(12):2239-2261. PubMed ID: 28204845
[TBL] [Abstract][Full Text] [Related]
18. Improving miRNA Target Prediction Using CLASH Data.
Li X; Hu H
Methods Mol Biol; 2019; 1970():75-83. PubMed ID: 30963489
[TBL] [Abstract][Full Text] [Related]
19. Identification and characterization of microRNAs in Eucheuma denticulatum by high-throughput sequencing and bioinformatics analysis.
Gao F; Nan F; Feng J; Lv J; Liu Q; Xie S
RNA Biol; 2016; 13(3):343-52. PubMed ID: 26717154
[TBL] [Abstract][Full Text] [Related]
20. Analysis of microRNA profile of Anopheles sinensis by deep sequencing and bioinformatic approaches.
Feng X; Zhou X; Zhou S; Wang J; Hu W
Parasit Vectors; 2018 Mar; 11(1):172. PubMed ID: 29530087
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
