Genomics & Informatics

Korea Genome Organization (한국유전체학회)
권호 표지
DOI QR코드

DOI QR Code

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

  • Received : 2019.02.12
  • Accepted : 2019.03.11
  • Published : 2019.03.31
Download PDF
⟨ Previous Next ⟩

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

References

  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. https://doi.org/10.1186/1755-8794-4-8
  2. Farazi TA, Hoell JI, Morozov P, Tuschl T. MicroRNAs in human cancer. Adv Exp Med Biol 2013;774:1-20. https://doi.org/10.1007/978-94-007-5590-1_1
  3. Kang SM, Lee HJ. MicroRNAs in human lung cancer. Exp Biol Med (Maywood) 2014;239:1505-1513. https://doi.org/10.1177/1535370214533887
  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. https://doi.org/10.12659/MSM.901191
  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. https://doi.org/10.1016/j.cell.2004.12.035
  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. https://doi.org/10.1093/nar/gkq1107
  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. https://doi.org/10.1186/s12859-018-2070-0
  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. https://doi.org/10.1111/j.1467-9868.2005.00503.x