These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

210 related articles for article (PubMed ID: 24930140)

  • 1. miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data.
    Lei J; Sun Y
    Bioinformatics; 2014 Oct; 30(19):2837-9. PubMed ID: 24930140
    [TBL] [Abstract][Full Text] [Related]  

  • 2. TarHunter, a tool for predicting conserved microRNA targets and target mimics in plants.
    Ma X; Liu C; Gu L; Mo B; Cao X; Chen X
    Bioinformatics; 2018 May; 34(9):1574-1576. PubMed ID: 29236948
    [TBL] [Abstract][Full Text] [Related]  

  • 3. miRA: adaptable novel miRNA identification in plants using small RNA sequencing data.
    Evers M; Huttner M; Dueck A; Meister G; Engelmann JC
    BMC Bioinformatics; 2015 Nov; 16():370. PubMed ID: 26542525
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA.
    Zhang T; Zhai J; Zhang X; Ling L; Li M; Xie S; Song M; Ma C
    Genomics Proteomics Bioinformatics; 2022 Jun; 20(3):557-567. PubMed ID: 34332120
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MTide: an integrated tool for the identification of miRNA-target interaction in plants.
    Zhang Z; Jiang L; Wang J; Gu P; Chen M
    Bioinformatics; 2015 Jan; 31(2):290-1. PubMed ID: 25256573
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A survey of software tools for microRNA discovery and characterization using RNA-seq.
    Bortolomeazzi M; Gaffo E; Bortoluzzi S
    Brief Bioinform; 2019 May; 20(3):918-930. PubMed ID: 29126230
    [TBL] [Abstract][Full Text] [Related]  

  • 7. mirExplorer: detecting microRNAs from genome and next generation sequencing data using the AdaBoost method with transition probability matrix and combined features.
    Guan DG; Liao JY; Qu ZH; Zhang Y; Qu LH
    RNA Biol; 2011; 8(5):922-34. PubMed ID: 21881406
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data.
    An J; Lai J; Sajjanhar A; Lehman ML; Nelson CC
    BMC Bioinformatics; 2014 Aug; 15(1):275. PubMed ID: 25117656
    [TBL] [Abstract][Full Text] [Related]  

  • 10. ShortStack: comprehensive annotation and quantification of small RNA genes.
    Axtell MJ
    RNA; 2013 Jun; 19(6):740-51. PubMed ID: 23610128
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The use of high-throughput sequencing methods for plant microRNA research.
    Ma X; Tang Z; Qin J; Meng Y
    RNA Biol; 2015; 12(7):709-19. PubMed ID: 26016494
    [TBL] [Abstract][Full Text] [Related]  

  • 12. miR-MaGiC improves quantification accuracy for small RNA-seq.
    Russell PH; Vestal B; Shi W; Rudra PD; Dowell R; Radcliffe R; Saba L; Kechris K
    BMC Res Notes; 2018 May; 11(1):296. PubMed ID: 29764489
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Highly efficient ligation of small RNA molecules for microRNA quantitation by high-throughput sequencing.
    Lee JE; Yi R
    J Vis Exp; 2014 Nov; (93):e52095. PubMed ID: 25490151
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computational evidence for hundreds of non-conserved plant microRNAs.
    Lindow M; Krogh A
    BMC Genomics; 2005 Sep; 6():119. PubMed ID: 16159385
    [TBL] [Abstract][Full Text] [Related]  

  • 15. OSA: a fast and accurate alignment tool for RNA-Seq.
    Hu J; Ge H; Newman M; Liu K
    Bioinformatics; 2012 Jul; 28(14):1933-4. PubMed ID: 22592379
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Computational analysis of miRNA targets in plants: current status and challenges.
    Dai X; Zhuang Z; Zhao PX
    Brief Bioinform; 2011 Mar; 12(2):115-21. PubMed ID: 20858738
    [TBL] [Abstract][Full Text] [Related]  

  • 17. miRDeep-P2: accurate and fast analysis of the microRNA transcriptome in plants.
    Kuang Z; Wang Y; Li L; Yang X
    Bioinformatics; 2019 Jul; 35(14):2521-2522. PubMed ID: 30521000
    [TBL] [Abstract][Full Text] [Related]  

  • 18. miR-RACE: an effective approach to accurately determine the sequence of computationally identified miRNAs.
    Wang C; Fang J
    Methods Mol Biol; 2015; 1296():109-18. PubMed ID: 25791595
    [TBL] [Abstract][Full Text] [Related]  

  • 19. miRge 2.0 for comprehensive analysis of microRNA sequencing data.
    Lu Y; Baras AS; Halushka MK
    BMC Bioinformatics; 2018 Jul; 19(1):275. PubMed ID: 30153801
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Mirnovo: genome-free prediction of microRNAs from small RNA sequencing data and single-cells using decision forests.
    Vitsios DM; Kentepozidou E; Quintais L; Benito-GutiƩrrez E; van Dongen S; Davis MP; Enright AJ
    Nucleic Acids Res; 2017 Dec; 45(21):e177. PubMed ID: 29036314
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.