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Hierarchical structural component modeling of microRNA-mRNA integration analysis
Cited 11 time in
Web of Science
Cited 13 time in Scopus
- Authors
- Issue Date
- 2018-05-08
- Publisher
- BioMed Central
- Citation
- BMC Bioinformatics, 19(Suppl 4):75
- Keywords
- miRNA ; mRNA ; Integration analysis ; Generalized Structured Component Analysis ; GSCA ; Hierarchical ; structured component analysis of miRNA-mRNA integration ; HisCoM-mimi
- Abstract
- Background
Identification of multi-markers is one of the most challenging issues in personalized medicine era. Nowadays, many different types of omics data are generated from the same subject. Although many methods endeavor to identify candidate markers, for each type of omics data, few or none can facilitate such identification.
Results
It is well known that microRNAs affect phenotypes only indirectly, through regulating mRNA expression and/or protein translation. Toward addressing this issue, we suggest a hierarchical structured component analysis of microRNA-mRNA integration (HisCoM-mimi) model that accounts for this biological relationship, to efficiently study and identify such integrated markers. In simulation studies, HisCoM-mimi showed the better performance than the other three methods. Also, in real data analysis, HisCoM-mimi successfully identified more gives more informative miRNA-mRNA integration sets relationships for pancreatic ductal adenocarcinoma (PDAC) diagnosis, compared to the other methods.
Conclusion
As exemplified by an application to pancreatic cancer data, our proposed model effectively identified integrated miRNA/target mRNA pairs as markers for early diagnosis, providing a much broader biological interpretation.
- ISSN
- 1471-2105
- Language
- English
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