WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting
An increasing number of experiments had verified that miRNA expression is related to human diseases. The miRNA expression profile may be an indicator of clinical diagnosis and provides a new direction for the prevention and treatment of complex diseases. In this work, we present a weighted voting-ba...
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2021-09-01
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doaj-38c11e6e671044cb8f4a5388391b18c22021-09-29T05:43:59ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-09-011210.3389/fgene.2021.742992742992WVMDA: Predicting miRNA–Disease Association Based on Weighted VotingZhen-Wei Zhang0Zhen Gao1Chun-Hou Zheng2Chun-Hou Zheng3Lei Li4Su-Min Qi5Yu-Tian Wang6School of Cyberspace Security, Qufu Normal University, Qufu, ChinaSchool of Computer Science and Technology, Anhui University, Hefei, ChinaSchool of Cyberspace Security, Qufu Normal University, Qufu, ChinaSchool of Computer Science and Technology, Anhui University, Hefei, ChinaSchool of Cyberspace Security, Qufu Normal University, Qufu, ChinaSchool of Cyberspace Security, Qufu Normal University, Qufu, ChinaSchool of Cyberspace Security, Qufu Normal University, Qufu, ChinaAn increasing number of experiments had verified that miRNA expression is related to human diseases. The miRNA expression profile may be an indicator of clinical diagnosis and provides a new direction for the prevention and treatment of complex diseases. In this work, we present a weighted voting-based model for predicting miRNA–disease association (WVMDA). To reasonably build a network of similarity, we established credibility similarity based on the reliability of known associations and used it to improve the original incomplete similarity. To eliminate noise interference as much as possible while maintaining more reliable similarity information, we developed a filter. More importantly, to ensure the fairness and efficiency of weighted voting, we focus on the design of weighting. Finally, cross-validation experiments and case studies are undertaken to verify the efficacy of the proposed model. The results showed that WVMDA could efficiently identify miRNAs associated with the disease.https://www.frontiersin.org/articles/10.3389/fgene.2021.742992/fullmiRNA-disease associationcredibility similarityweighted votingmiRNAdisease |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhen-Wei Zhang Zhen Gao Chun-Hou Zheng Chun-Hou Zheng Lei Li Su-Min Qi Yu-Tian Wang |
spellingShingle |
Zhen-Wei Zhang Zhen Gao Chun-Hou Zheng Chun-Hou Zheng Lei Li Su-Min Qi Yu-Tian Wang WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting Frontiers in Genetics miRNA-disease association credibility similarity weighted voting miRNA disease |
author_facet |
Zhen-Wei Zhang Zhen Gao Chun-Hou Zheng Chun-Hou Zheng Lei Li Su-Min Qi Yu-Tian Wang |
author_sort |
Zhen-Wei Zhang |
title |
WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting |
title_short |
WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting |
title_full |
WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting |
title_fullStr |
WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting |
title_full_unstemmed |
WVMDA: Predicting miRNA–Disease Association Based on Weighted Voting |
title_sort |
wvmda: predicting mirna–disease association based on weighted voting |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Genetics |
issn |
1664-8021 |
publishDate |
2021-09-01 |
description |
An increasing number of experiments had verified that miRNA expression is related to human diseases. The miRNA expression profile may be an indicator of clinical diagnosis and provides a new direction for the prevention and treatment of complex diseases. In this work, we present a weighted voting-based model for predicting miRNA–disease association (WVMDA). To reasonably build a network of similarity, we established credibility similarity based on the reliability of known associations and used it to improve the original incomplete similarity. To eliminate noise interference as much as possible while maintaining more reliable similarity information, we developed a filter. More importantly, to ensure the fairness and efficiency of weighted voting, we focus on the design of weighting. Finally, cross-validation experiments and case studies are undertaken to verify the efficacy of the proposed model. The results showed that WVMDA could efficiently identify miRNAs associated with the disease. |
topic |
miRNA-disease association credibility similarity weighted voting miRNA disease |
url |
https://www.frontiersin.org/articles/10.3389/fgene.2021.742992/full |
work_keys_str_mv |
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