Browse > Article
http://dx.doi.org/10.5808/GI.2019.17.1.e10

HisCoM-mimi: software for hierarchical structural component analysis for miRNA-mRNA integration model for binary phenotypes  

Kim, Yongkang (Department of Statistics, Seoul National University)
Park, Taesung (Department of Statistics, Seoul National University)
Abstract
To identify miRNA-mRNA interaction pairs associated with binary phenotypes, we propose a hierarchical structural component model for miRNA-mRNA integration (HisCoM-mimi). Information on known mRNA targets provided by TargetScan is used to perform HisCoM-mimi. However, multiple databases can be used to find miRNA-mRNA signatures with known biological information through different algorithms. To take these additional databases into account, we present our advanced application software for HisCoM-mimi for binary phenotypes. The proposed HisCoM-mimi supports both TargetScan and miRTarBase, which provides manually-verified information initially gathered by text-mining the literature. By integrating information from miRTarBase into HisCoM-mimi, a broad range of target information derived from the research literature can be analyzed. Another improvement of the new HisCoM-mimi approach is the inclusion of updated algorithms to provide the lasso and elastic-net penalties for users who want to fit a model with a smaller number of selected miRNAs and mRNAs. We expect that our HisCoM-mimi software will make advanced methods accessible to researchers who want to identify miRNA-mRNA interaction pairs related with binary phenotypes.
Keywords
integration analysis; miRNA; miRNA database; mRNA;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Cho JH, Gelinas R, Wang K, Etheridge A, Piper MG, Batte K, et al. Systems biology of interstitial lung diseases: integration of mRNA and microRNA expression changes. BMC Med Genomics 2011;4:8.   DOI
2 Farazi TA, Hoell JI, Morozov P, Tuschl T. MicroRNAs in human cancer. Adv Exp Med Biol 2013;774:1-20.   DOI
3 Kang SM, Lee HJ. MicroRNAs in human lung cancer. Exp Biol Med (Maywood) 2014;239:1505-1513.   DOI
4 Shi Y, Yang F, Wei S, Xu G. Identification of key genes affecting results of hyperthermia in osteosarcoma based on integrative ChIP-Seq/TargetScan analysis. Med Sci Monit 2017;23:2042-2048.   DOI
5 Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005;120:15-20.   DOI
6 Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, et al. miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic Acids Res 2011;39:D163-D169.   DOI
7 Kim Y, Lee S, Choi S, Jang JY, Park T. Hierarchical structural component modeling of microRNA-mRNA integration analysis. BMC Bioinformatics 2018;19:75.   DOI
8 Tibshirani R. Regression shrinkage and selection via the Lasso. J R Stat Soc Series B Methodol 1996;58:267-288.
9 Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc B 2005;67:301-320.   DOI