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MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here present a user-friendly pure Java-based software package, SRICATs, which enable researchers to perform all steps of plant miRNA analysis based on convolutional neural network methods. SRICATs outperforms currently popular software tools on the test data from five plant species: Oryza sativa, Arabidopsis thaliana, Sorghum bicolor, Chlamydomonas reinhardtii and Physcomitrella patens.
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