miRLocator applies machine learning algorithms to accurately predict the localization of most likely miRNAs within their pre-miRNAs. One major strength of miRLocator is the fact that the machine learning-based miRNA prediction model can be automatically trained using a set of miRNAs of particular interest, with informative features extracted from miRNA-miRNA* duplexes and the optimized ratio between positive and negative samples.

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Cui H, Zhai J, Ma C. miRLocator: Machine Learning-Based Prediction of Mature MicroRNAs within Plant Pre-miRNA Sequences.[J]. Plos One, 2015, 10(11):e0142753.

Zhang T, Ju L, Zhai J, Song Y, Song J, Ma C. miRLocator: A Python Implementation and Web Server for Predicting miRNAs from Pre-miRNA Sequences [M]. Plant MicroRNAs, 2019, 89-97.