期刊
JOURNAL OF BIOMEDICAL SEMANTICS
卷 8, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s13326-017-0140-2
关键词
Functional similarity; Similarity score; Disease sets; Disease-miRNA relationships
资金
- Major State Research Development Program of China [2016YFC1202302]
- National Natural Science Foundation of China [61502125]
- Heilongjiang Postdoctoral Fund [LBH-Z15179]
- China Postdoctoral Science Foundation [2016 M590291]
Background: Functional similarity between molecules results in similar phenotypes, such as diseases. Therefore, it is an effective way to reveal the function of molecules based on their induced diseases. However, the lack of a tool for obtaining the similarity score of pair-wise disease sets (SSDS) limits this type of application. Results: Here, we introduce DisSetSim, an online system to solve this problem in this article. Five state-of-the-art methods involving Resnik's, Lin's, Wang's, PSB, and SemFunSim methods were implemented to measure the similarity score of pairwise diseases (SSD) first. And then pair-wise-best pairs-average (PWBPA) method was implemented to calculated the SSDS by the SSD. The system was applied for calculating the functional similarity of miRNAs based on their induced disease sets. The results were further used to predict potential disease-miRNA relationships. Conclusions: The high area under the receiver operating characteristic curve AUC (0.9296) based on leave-one-out cross validation shows that the PWBPA method achieves a high true positive rate and a low false positive rate. The system can be accessed from http://www.bio-annotation.cn:8080/DisSetSim/.
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