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miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets

Author

Listed:
  • Tzu-Pin Lu
  • Chien-Yueh Lee
  • Mong-Hsun Tsai
  • Yu-Chiao Chiu
  • Chuhsing Kate Hsiao
  • Liang-Chuan Lai
  • Eric Y Chuang

Abstract

Background: Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses. Results: First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted. Conclusions: MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.

Suggested Citation

  • Tzu-Pin Lu & Chien-Yueh Lee & Mong-Hsun Tsai & Yu-Chiao Chiu & Chuhsing Kate Hsiao & Liang-Chuan Lai & Eric Y Chuang, 2012. "miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-10, August.
    • Handle: RePEc:plo:pone00:0042390
    DOI: 10.1371/journal.pone.0042390
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    Cited by:

    1. Schimek Michael G. & Švendová Vendula & Budinská Eva & Kugler Karl G. & Ding Jie & Lin Shili, 2015. "TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(3), pages 311-316, June.
    2. Sophie L Wardle & Mark E S Bailey & Audrius Kilikevicius & Dalia Malkova & Richard H Wilson & Tomas Venckunas & Colin N Moran, 2015. "Plasma MicroRNA Levels Differ between Endurance and Strength Athletes," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.

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