AUTHOR=Min Hui , Xin Xiao-Hong , Gao Chu-Qiao , Wang Likun , Du Pu-Feng 

TITLE=XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.877409

DOI=10.3389/fgene.2022.877409

ISSN=1664-8021

ABSTRACT=MicroRNAs (miRNAs) play vital roles in gene expression regulations. Identification of essential miRNAs is of fundamental importance in understanding their cellular functions. Experimental methods for identifying essential miRNAs are always costly and time-consuming. Therefore, computational methods are considered as alternative approaches. Currently, only a handful of studies focused on predicting essential miRNAs. In this work, we propose to predict essential miRNAs using XGBoost framework with CART (Classification and Regression Trees) on various types of sequence-based features. We name this method as XGEM (XGBoost for Essential MiRNAs). The prediction performance of XGEM is promising. In the comparison to other state-of-the art methods, XGEM performed the best, indicating its potential in identifying essential miRNAs. All codes and datasets of this study are deposited in a GitHub repository (https://github.com/minhui803/XGEM).