A novel approach for predicting disease-lncRNA associations based on the distance correlation set and information of the miRNAs
type: Item
instance of: scholarly article
title: A novel approach for predicting disease-lncRNA associations based on the distance correlation set and information of the miRNAs
zbMATH Open document ID: 1411.92118
DOI: 10.1155/2018/6747453
author: Haochen Zhao
author: Linai Kuang
author: Lei Wang
author: Zhanwei Xuan
published in: Computational \& Mathematical Methods in Medicine
publication date: 2019-03-27T00:00:00Z
review text: Summary: Recently, accumulating laboratorial studies have indicated that plenty of long noncoding RNAs (lncRNAs) play important roles in various biological processes and are associated with many complex human diseases. Therefore, developing powerful computational models to predict correlation between lncRNAs and diseases based on heterogeneous biological datasets will be important. However, there are few approaches to calculating and analyzing lncRNA-disease associations on the basis of information about miRNAs. In this article, a new computational method based on distance correlation set is developed to predict lncRNA-disease associations (DCSLDA). Comparing with existing state-of-the-art methods, we found that the major novelty of DCSLDA lies in the introduction of lncRNA-miRNA-disease network and distance correlation set; thus DCSLDA can be applied to predict potential lncRNA-disease associations without requiring any known disease-lncRNA associations. Simulation results show that DCSLDA can significantly improve previous existing models with reliable AUC of 0.8517 in the leave-one-out cross-validation. Furthermore, while implementing DCSLDA to prioritize candidate lncRNAs for three important cancers, in the first 0.5\% of forecast results, 17 predicted associations are verified by other independent studies and biological experimental studies. Hence, it is anticipated that DCSLDA could be a great addition to the biomedical research field.
Mathematics Subject Classification ID: 92C40
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 92C42
zbMATH DE Number: 7043208
zbMATH Keywords: disease-lncRNA associations
zbMATH Keywords: distance correlation set
zbMATH Keywords: miRNAs
describes a project that uses: lncRNAdb
describes a project that uses: starBase
describes a project that uses: LncDisease
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/6747453
OpenAlex ID: W2810992649
Wikidata QID: Q90477586
DBLP publication ID: journals/cmmm/ZhaoKWX18
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description: scientific article; zbMATH DE number 7043208