Improved low-rank matrix recovery method for predicting miRNA-disease association

Abstract MicroRNAs (miRNAs) performs crucial roles in various human diseases, but miRNA-related pathogenic mechanisms remain incompletely understood. Revealing the potential relationship between miRNAs and diseases is a critical problem in biomedical research. Considering limitation of existing comp...

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Autores principales:	Li Peng, Manman Peng, Bo Liao, Guohua Huang, Wei Liang, Keqin Li
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f4af1f5773e542e4858c49bbf482e52f
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spelling	oai:doaj.org-article:f4af1f5773e542e4858c49bbf482e52f2021-12-02T16:08:12ZImproved low-rank matrix recovery method for predicting miRNA-disease association10.1038/s41598-017-06201-32045-2322https://doaj.org/article/f4af1f5773e542e4858c49bbf482e52f2017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06201-3https://doaj.org/toc/2045-2322Abstract MicroRNAs (miRNAs) performs crucial roles in various human diseases, but miRNA-related pathogenic mechanisms remain incompletely understood. Revealing the potential relationship between miRNAs and diseases is a critical problem in biomedical research. Considering limitation of existing computational approaches, we develop improved low-rank matrix recovery (ILRMR) for miRNA-disease association prediction. ILRMR is a global method that can simultaneously prioritize potential association for all diseases and does not require negative samples. ILRMR can also identify promising miRNAs for investigating diseases without any known related miRNA. By integrating miRNA-miRNA similarity information, disease-disease similarity information, and miRNA family information to matrix recovery, ILRMR performs better than other methods in cross validation and case studies.Li PengManman PengBo LiaoGuohua HuangWei LiangKeqin LiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Li Peng Manman Peng Bo Liao Guohua Huang Wei Liang Keqin Li Improved low-rank matrix recovery method for predicting miRNA-disease association
description	Abstract MicroRNAs (miRNAs) performs crucial roles in various human diseases, but miRNA-related pathogenic mechanisms remain incompletely understood. Revealing the potential relationship between miRNAs and diseases is a critical problem in biomedical research. Considering limitation of existing computational approaches, we develop improved low-rank matrix recovery (ILRMR) for miRNA-disease association prediction. ILRMR is a global method that can simultaneously prioritize potential association for all diseases and does not require negative samples. ILRMR can also identify promising miRNAs for investigating diseases without any known related miRNA. By integrating miRNA-miRNA similarity information, disease-disease similarity information, and miRNA family information to matrix recovery, ILRMR performs better than other methods in cross validation and case studies.
format	article
author	Li Peng Manman Peng Bo Liao Guohua Huang Wei Liang Keqin Li
author_facet	Li Peng Manman Peng Bo Liao Guohua Huang Wei Liang Keqin Li
author_sort	Li Peng
title	Improved low-rank matrix recovery method for predicting miRNA-disease association
title_short	Improved low-rank matrix recovery method for predicting miRNA-disease association
title_full	Improved low-rank matrix recovery method for predicting miRNA-disease association
title_fullStr	Improved low-rank matrix recovery method for predicting miRNA-disease association
title_full_unstemmed	Improved low-rank matrix recovery method for predicting miRNA-disease association
title_sort	improved low-rank matrix recovery method for predicting mirna-disease association
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/f4af1f5773e542e4858c49bbf482e52f
work_keys_str_mv	AT lipeng improvedlowrankmatrixrecoverymethodforpredictingmirnadiseaseassociation AT manmanpeng improvedlowrankmatrixrecoverymethodforpredictingmirnadiseaseassociation AT boliao improvedlowrankmatrixrecoverymethodforpredictingmirnadiseaseassociation AT guohuahuang improvedlowrankmatrixrecoverymethodforpredictingmirnadiseaseassociation AT weiliang improvedlowrankmatrixrecoverymethodforpredictingmirnadiseaseassociation AT keqinli improvedlowrankmatrixrecoverymethodforpredictingmirnadiseaseassociation
_version_	1718384631534845952

Improved low-rank matrix recovery method for predicting miRNA-disease association

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