马闯等《Methods Mol Biol.》2019

　　论文题目：miRLocator: A Python Implementation and Web Server for Predicting miRNAs from Pre-miRNA Sequences

　　论文作者: Zhang T, Ju L, Zhai J, Song Y, Song J, Ma C.

　　论文摘要：microRNAs (miRNAs) are short, noncoding regulatory RNAs derived from hairpin precursors (pre-miRNAs). In synergy with experimental approaches, computational approaches have become an invaluable tool for identifying miRNAs at the genome scale. We have recently reported a method called miRLocator, which applies machine learning algorithms to accurately predict the localization of most likely miRNAswithin 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. Here, we present a detailed protocol for miRLocator that performs the training and prediction processes using a python implementation and web interface. The source codes, web interface, and manual documents are freely available to academic users at https://github.com/cma2015/miRLocator

　　论文链接：https://link.springer.com/protocol/10.1007/978-1-4939-9042-9_6