4.7 Article

miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data

期刊

BIOINFORMATICS
卷 30, 期 19, 页码 2837-2839

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OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu380

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资金

  1. NSF CAREER Grant [DBI-0953738]
  2. NSF [IOS-1126998]
  3. Direct For Biological Sciences
  4. Division Of Integrative Organismal Systems [1126998] Funding Source: National Science Foundation
  5. Direct For Biological Sciences
  6. Div Of Biological Infrastructure [0953738] Funding Source: National Science Foundation

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A Summary: Plant microRNA prediction tools that use small RNA-sequencing data are emerging quickly. These existing tools have at least one of the following problems: (i) high false-positive rate; (ii) long running time; (iii) work only for genomes in their databases; (iv) hard to install or use. We developed miR-PREFeR (miRNA PREdiction From small RNA-Seq data), which uses expression patterns of miRNA and follows the criteria for plant microRNA annotation to accurately predict plant miRNAs from one or more small RNA-Seq data samples of the same species. We tested miR-PREFeR on several plant species. The results show that miR-PREFeR is sensitive, accurate, fast and has low-memory footprint.

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