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sherry_zhang
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4Â¥2015-11-04 16:59:51
yingyangyang
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»ùÓÚСRNA-SeqÊý¾ÝµÄÖ²ÎïmiRNAÔ¤²â¹¤¾ß miR-PREFeR: an accurate, fast, and easy-to-use plant miRNA prediction tool using small RNA-Seq data. Abstract Summary: Plant microRNA prediction tools that utilize small RNA sequencing data are emerging quickly. These existing tools have at least one of the following problems: 1. high false positive rate; 2. long running time; 3. work only for genomes in their databases; 4. hard to install or use. We develop miR-PREFeR (miRNA PREdiction From small RNA-Seq data), which utilizes 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. Availability: https://github.com/hangelwen/miR-PREFeR http://bioinformatics.oxfordjour ... ics.btu380.abstract |
2Â¥2015-08-18 15:15:24
sherry_zhang
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3Â¥2015-08-21 09:13:58
5Â¥2015-11-05 07:43:56














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