![](/images/graphics-bg.png)
A Novel Model for Predicting Associations between Diseases and LncRNA-miRNA Pairs Based on a Newly Constructed Bipartite Network
Joint Authors
Wang, Lei
Xuan, Zhanwei
Ping, Pengyao
Zhou, Shunxian
Pei, Tingrui
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-06
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Motivation.
Increasing studies have demonstrated that many human complex diseases are associated with not only microRNAs, but also long-noncoding RNAs (lncRNAs).
LncRNAs and microRNA play significant roles in various biological processes.
Therefore, developing effective computational models for predicting novel associations between diseases and lncRNA-miRNA pairs (LMPairs) will be beneficial to not only the understanding of disease mechanisms at lncRNA-miRNA level and the detection of disease biomarkers for disease diagnosis, treatment, prognosis, and prevention, but also the understanding of interactions between diseases and LMPairs at disease level.
Results.
It is well known that genes with similar functions are often associated with similar diseases.
In this article, a novel model named PADLMP for predicting associations between diseases and LMPairs is proposed.
In this model, a Disease-LncRNA-miRNA (DLM) tripartite network was designed firstly by integrating the lncRNA-disease association network and miRNA-disease association network; then we constructed the disease-LMPairs bipartite association network based on the DLM network and lncRNA-miRNA association network; finally, we predicted potential associations between diseases and LMPairs based on the newly constructed disease-LMPair network.
Simulation results show that PADLMP can achieve AUCs of 0.9318, 0.9090 ± 0.0264, and 0.8950 ± 0.0027 in the LOOCV, 2-fold, and 5-fold cross validation framework, respectively, which demonstrate the reliable prediction performance of PADLMP.
American Psychological Association (APA)
Zhou, Shunxian& Xuan, Zhanwei& Wang, Lei& Ping, Pengyao& Pei, Tingrui. 2018. A Novel Model for Predicting Associations between Diseases and LncRNA-miRNA Pairs Based on a Newly Constructed Bipartite Network. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1132103
Modern Language Association (MLA)
Zhou, Shunxian…[et al.]. A Novel Model for Predicting Associations between Diseases and LncRNA-miRNA Pairs Based on a Newly Constructed Bipartite Network. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1132103
American Medical Association (AMA)
Zhou, Shunxian& Xuan, Zhanwei& Wang, Lei& Ping, Pengyao& Pei, Tingrui. A Novel Model for Predicting Associations between Diseases and LncRNA-miRNA Pairs Based on a Newly Constructed Bipartite Network. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1132103
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132103