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

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...

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Detalles Bibliográficos
Autores principales: Min, Hui, Xin, Xiao-Hong, Gao, Chu-Qiao, Wang, Likun, Du, Pu-Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996062/
https://www.ncbi.nlm.nih.gov/pubmed/35419029
http://dx.doi.org/10.3389/fgene.2022.877409
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author Min, Hui
Xin, Xiao-Hong
Gao, Chu-Qiao
Wang, Likun
Du, Pu-Feng
author_facet Min, Hui
Xin, Xiao-Hong
Gao, Chu-Qiao
Wang, Likun
Du, Pu-Feng
author_sort Min, Hui
collection PubMed
description 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 are focused on predicting essential miRNAs. In this work, we proposed to predict essential miRNAs using the XGBoost framework with CART (Classification and Regression Trees) on various types of sequence-based features. We named this method as XGEM (XGBoost for essential miRNAs). The prediction performance of XGEM is promising. In comparison with other state-of-the-art methods, XGEM performed the best, indicating its potential in identifying essential miRNAs.
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spelling pubmed-89960622022-04-12 XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm Min, Hui Xin, Xiao-Hong Gao, Chu-Qiao Wang, Likun Du, Pu-Feng Front Genet Genetics 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 are focused on predicting essential miRNAs. In this work, we proposed to predict essential miRNAs using the XGBoost framework with CART (Classification and Regression Trees) on various types of sequence-based features. We named this method as XGEM (XGBoost for essential miRNAs). The prediction performance of XGEM is promising. In comparison with other state-of-the-art methods, XGEM performed the best, indicating its potential in identifying essential miRNAs. Frontiers Media S.A. 2022-03-28 /pmc/articles/PMC8996062/ /pubmed/35419029 http://dx.doi.org/10.3389/fgene.2022.877409 Text en Copyright © 2022 Min, Xin, Gao, Wang and Du. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Min, Hui
Xin, Xiao-Hong
Gao, Chu-Qiao
Wang, Likun
Du, Pu-Feng
XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
title XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
title_full XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
title_fullStr XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
title_full_unstemmed XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
title_short XGEM: Predicting Essential miRNAs by the Ensembles of Various Sequence-Based Classifiers With XGBoost Algorithm
title_sort xgem: predicting essential mirnas by the ensembles of various sequence-based classifiers with xgboost algorithm
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996062/
https://www.ncbi.nlm.nih.gov/pubmed/35419029
http://dx.doi.org/10.3389/fgene.2022.877409
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