Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association

Abstract microRNAs (miRNAs) mutation and maladjustment are related to the occurrence and development of human diseases. Studies on disease-associated miRNA have contributed to disease diagnosis and treatment. To address the problems, such as low prediction accuracy and failure to predict the relatio...

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Autores principales:	Min Chen, Bo Liao, Zejun Li
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3d369e26a43644018b5625c1ab4fb33a
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spelling	oai:doaj.org-article:3d369e26a43644018b5625c1ab4fb33a2021-12-02T15:08:19ZGlobal Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association10.1038/s41598-018-24532-72045-2322https://doaj.org/article/3d369e26a43644018b5625c1ab4fb33a2018-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-24532-7https://doaj.org/toc/2045-2322Abstract microRNAs (miRNAs) mutation and maladjustment are related to the occurrence and development of human diseases. Studies on disease-associated miRNA have contributed to disease diagnosis and treatment. To address the problems, such as low prediction accuracy and failure to predict the relationship between new miRNAs and diseases and so on, we design a Laplacian score of graphs to calculate the global similarity of networks and propose a Global Similarity method based on a Two-tier Random Walk for the prediction of miRNA–disease association (GSTRW) to reveal the correlation between miRNAs and diseases. This method is a global approach that can simultaneously predict the correlation between all diseases and miRNAs in the absence of negative samples. Experimental results reveal that this method is better than existing approaches in terms of overall prediction accuracy and ability to predict orphan diseases and novel miRNAs. A case study on GSTRW for breast cancer and conlon cancer is also conducted, and the majority of miRNA–disease association can be verified by our experiment. This study indicates that this method is feasible and effective.Min ChenBo LiaoZejun LiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-16 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Min Chen Bo Liao Zejun Li Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association
description	Abstract microRNAs (miRNAs) mutation and maladjustment are related to the occurrence and development of human diseases. Studies on disease-associated miRNA have contributed to disease diagnosis and treatment. To address the problems, such as low prediction accuracy and failure to predict the relationship between new miRNAs and diseases and so on, we design a Laplacian score of graphs to calculate the global similarity of networks and propose a Global Similarity method based on a Two-tier Random Walk for the prediction of miRNA–disease association (GSTRW) to reveal the correlation between miRNAs and diseases. This method is a global approach that can simultaneously predict the correlation between all diseases and miRNAs in the absence of negative samples. Experimental results reveal that this method is better than existing approaches in terms of overall prediction accuracy and ability to predict orphan diseases and novel miRNAs. A case study on GSTRW for breast cancer and conlon cancer is also conducted, and the majority of miRNA–disease association can be verified by our experiment. This study indicates that this method is feasible and effective.
format	article
author	Min Chen Bo Liao Zejun Li
author_facet	Min Chen Bo Liao Zejun Li
author_sort	Min Chen
title	Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association
title_short	Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association
title_full	Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association
title_fullStr	Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association
title_full_unstemmed	Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association
title_sort	global similarity method based on a two-tier random walk for the prediction of microrna–disease association
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/3d369e26a43644018b5625c1ab4fb33a
work_keys_str_mv	AT minchen globalsimilaritymethodbasedonatwotierrandomwalkforthepredictionofmicrornadiseaseassociation AT boliao globalsimilaritymethodbasedonatwotierrandomwalkforthepredictionofmicrornadiseaseassociation AT zejunli globalsimilaritymethodbasedonatwotierrandomwalkforthepredictionofmicrornadiseaseassociation
_version_	1718388180189708288

Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA–Disease Association

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