lncRNA-disease association prediction based on latent factor model and projection

Abstract Computer aided research of lncRNA-disease association is an important way to study the development of lncRNA-disease. The correlation analysis of existing data, the establishment of prediction model, prediction of unknown lncRNA-disease association, can make the biological experiment target...

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Main Authors: Bo Wang, Chao Zhang, Xiao-xin Du, Jian-fei Zhang
Format: Article
Language:English
Published: Nature Portfolio 2021-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-99493-5
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author Bo Wang
Chao Zhang
Xiao-xin Du
Jian-fei Zhang
author_facet Bo Wang
Chao Zhang
Xiao-xin Du
Jian-fei Zhang
author_sort Bo Wang
collection DOAJ
description Abstract Computer aided research of lncRNA-disease association is an important way to study the development of lncRNA-disease. The correlation analysis of existing data, the establishment of prediction model, prediction of unknown lncRNA-disease association, can make the biological experiment targeted, improve the accuracy of biological experiment. In this paper, a lncRNA-disease association prediction model based on latent factor model and projection is proposed (LFMP). This method uses lncRNA-miRNA association data and miRNA-disease association data to predict the unknown lncRNA-disease association, so this method does not need lncRNA-disease association data. The simulation results show that under the LOOCV framework, the AUC of LFMP can reach 0.8964. Better than the latest results. Through the case study of lung and colorectal tumors, LFMP can effectively infer the undetected lncRNA-disease association.
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spelling doaj.art-773e8f73e6c04adfb6520c47f30373612022-12-21T21:47:38ZengNature PortfolioScientific Reports2045-23222021-10-0111111010.1038/s41598-021-99493-5lncRNA-disease association prediction based on latent factor model and projectionBo Wang0Chao Zhang1Xiao-xin Du2Jian-fei Zhang3College of Computer and Control Engineering, Qiqihar UniversityCollege of Computer and Control Engineering, Qiqihar UniversityCollege of Computer and Control Engineering, Qiqihar UniversityCollege of Computer and Control Engineering, Qiqihar UniversityAbstract Computer aided research of lncRNA-disease association is an important way to study the development of lncRNA-disease. The correlation analysis of existing data, the establishment of prediction model, prediction of unknown lncRNA-disease association, can make the biological experiment targeted, improve the accuracy of biological experiment. In this paper, a lncRNA-disease association prediction model based on latent factor model and projection is proposed (LFMP). This method uses lncRNA-miRNA association data and miRNA-disease association data to predict the unknown lncRNA-disease association, so this method does not need lncRNA-disease association data. The simulation results show that under the LOOCV framework, the AUC of LFMP can reach 0.8964. Better than the latest results. Through the case study of lung and colorectal tumors, LFMP can effectively infer the undetected lncRNA-disease association.https://doi.org/10.1038/s41598-021-99493-5
spellingShingle Bo Wang
Chao Zhang
Xiao-xin Du
Jian-fei Zhang
lncRNA-disease association prediction based on latent factor model and projection
Scientific Reports
title lncRNA-disease association prediction based on latent factor model and projection
title_full lncRNA-disease association prediction based on latent factor model and projection
title_fullStr lncRNA-disease association prediction based on latent factor model and projection
title_full_unstemmed lncRNA-disease association prediction based on latent factor model and projection
title_short lncRNA-disease association prediction based on latent factor model and projection
title_sort lncrna disease association prediction based on latent factor model and projection
url https://doi.org/10.1038/s41598-021-99493-5
work_keys_str_mv AT bowang lncrnadiseaseassociationpredictionbasedonlatentfactormodelandprojection
AT chaozhang lncrnadiseaseassociationpredictionbasedonlatentfactormodelandprojection
AT xiaoxindu lncrnadiseaseassociationpredictionbasedonlatentfactormodelandprojection
AT jianfeizhang lncrnadiseaseassociationpredictionbasedonlatentfactormodelandprojection