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IDLDA: An Improved Diffusion Model for Predicting LncRNA-Disease Associations
Wang, Qi1,2; Yan, Guiying1,2
AbstractIt has been demonstrated that long non-coding RNAs (lncRNAs) play important roles in a variety of biological processes associated with human diseases. However, the identification of lncRNA-disease associations by experimental methods is time-consuming and labor-intensive. Computational methods provide an effective strategy to predict more potential lncRNA-disease associations to some degree. Based on the hypothesis that phenotypically similar diseases are often associated with functionally similar lncRNAs and vice versa, we developed an improved diffusion model to predict potential lncRNA-disease associations (IDLDA). As a result, our model performed well in the global and local cross-validations, which indicated that IDLDA had a great performance in predicting novel associations. Case studies of colon cancer, breast cancer, and gastric cancer were also implemented, all lncRNAs which ranked top 10 in both databases were verified by databases and related literature. The results showed that IDLDA might play a key role in biomedical research.
Keywordlong non-coding RNA disease association prediction computational prediction model diffusion model
Indexed BySCI
Funding ProjectNational Natural Science Foundation of China[11631014]
WOS Research AreaGenetics & Heredity
WOS SubjectGenetics & Heredity
WOS IDWOS:000504209400001
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Document Type期刊论文
Corresponding AuthorYan, Guiying
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Wang, Qi,Yan, Guiying. IDLDA: An Improved Diffusion Model for Predicting LncRNA-Disease Associations[J]. FRONTIERS IN GENETICS,2019,10:10.
APA Wang, Qi,&Yan, Guiying.(2019).IDLDA: An Improved Diffusion Model for Predicting LncRNA-Disease Associations.FRONTIERS IN GENETICS,10,10.
MLA Wang, Qi,et al."IDLDA: An Improved Diffusion Model for Predicting LncRNA-Disease Associations".FRONTIERS IN GENETICS 10(2019):10.
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