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A Novel Approach for Predicting Disease-lncRNA Associations Based on the Distance Correlation Set and Information of the miRNAs
Joint Authors
Wang, Lei
Xuan, Zhanwei
Zhao, Haochen
Kuang, Linai
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-06-26
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Zhao, Haochen& Kuang, Linai& Wang, Lei& Xuan, Zhanwei. 2018. A Novel Approach for Predicting Disease-lncRNA Associations Based on the Distance Correlation Set and Information of the miRNAs. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1132101
Modern Language Association (MLA)
Zhao, Haochen…[et al.]. A Novel Approach for Predicting Disease-lncRNA Associations Based on the Distance Correlation Set and Information of the miRNAs. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1132101
American Medical Association (AMA)
Zhao, Haochen& Kuang, Linai& Wang, Lei& Xuan, Zhanwei. A Novel Approach for Predicting Disease-lncRNA Associations Based on the Distance Correlation Set and Information of the miRNAs. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1132101
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132101