A Model Based on Random Walk with Restart to Predict CircRNA-Disease Associations on Heterogeneous Network

被引：28

作者：

Vural, Huseyin ^{[1
]}

Kaya, Mehmet ^{[2
]}

Alhajj, Reda ^{[3
]}

机构：

[1] Adiyaman Univ, Dept Comp Technol, Adiyaman, Turkey

[2] Firat Univ, Dept Comp Engn, Elazig, Turkey

[3] Istanbul Medipol Univ, Dept Comp Engn, Istanbul, Turkey

来源：

PROCEEDINGS OF THE 2019 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2019) | 2019年

关键词：

CircRNA Disease Association; Random; Walk; Prediction;

D O I：

10.1145/3341161.3343514

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recent studies show that circRNAs have critical roles in many biological processes. Knowing the associations between circRNAs and diseases may contribute to the understanding of the mechanism of circRNAs and to the diagnostic and therapeutic methods of diseases at the molecular level. A small number of computation models have been developed to estimate CircRNA-disease associations. Therefore, in this study, a computational model has been developed. Similarity matrices have been obtained for circRNA and disease respectively by applying gaussian on the data obtained from the circRNADisease database. Then, random walk with restart algorithm applied on the combined matrices. The AUC value was obtained by 5-fold cross validation is 0.861 and this demonstrates the reliability of the model.

引用

页码：929 / 932

页数：4

共 19 条

[1] Predicting lncRNA-disease associations and constructing lncRNA functional similarity network based on the information of miRNA [J].