A novel method to identify pre-microRNA in various species knowledge base

Abstract

More than 1/3 of human genes are regulated by microRNAs. The identification of microRNA (miRNA) is the precondition of discovering the regulatory mechanism of miRNA and developing the cure for genetic diseases. The traditional identification method is biological experiment, but it has the defects of long period, high cost, and missing the miRNAs that only exist in a specific period or low expression level. Therefore, to overcome these defects, machine learning method is applied to identify miRNAs. In this study, for identifying real and pseudo miRNAs and classifying different species, we extracted 98 dimensional features based on the primary and secondary structure, then we proposed the BP-Adaboost method to figure out the overfitting phenomenon of BP neural network by constructing multiple BP neural network classifiers and distributed weights to these classifiers. The novel method we proposed raised the accuracy and the stability. In this study, we verified the effectiveness and superiority over other methods by experiments.