Pharmaceutical Research

, Volume 28, Issue 12, pp 3101–3104 | Cite as

OMIT: A Domain-Specific Knowledge Base for MicroRNA Target Prediction

  • Jingshan HuangEmail author
  • Christopher Townsend
  • Dejing Dou
  • Haishan Liu
  • Ming Tan


Identification and characterization of the important roles microRNAs (miRNAs) perform in human cancer is an increasingly active research area. Unfortunately, prediction of miRNA target genes remains a challenging task to cancer researchers. Current processes are time-consuming, error-prone, and subject to biologists’ limited prior knowledge. Therefore, we propose a domain-specific knowledge base built upon Ontology for MicroRNA Targets (OMIT) to facilitate knowledge acquisition in miRNA target gene prediction. We describe the ontology design, semantic annotation and data integration, and user-friendly interface and conclude that the OMIT system can assist biologists in unraveling the important roles of miRNAs in human cancer. Thus, it will help clinicians make sound decisions when treating cancer patients.


human cancer knowledge acquisition knowledge base microRNA (miRNA) target ontology 



The authors would like to thank Hardik Shah and Robert Rudnick for helping in software implementation. The authors also appreciate the discussion with Patrick Hayes, Lei He, Wen-chang Lin, Hao Sun, and Xiaowei Wang.

Supplementary material

11095_2011_573_MOESM1_ESM.docx (258 kb)
ESM 1 (DOCX 257 kb)


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Jingshan Huang
    • 1
    Email author
  • Christopher Townsend
    • 1
  • Dejing Dou
    • 2
  • Haishan Liu
    • 2
  • Ming Tan
    • 3
    • 4
  1. 1.School of Computer and Information SciencesUniversity of South AlabamaMobileUSA
  2. 2.Department of Computer and Information ScienceUniversity of OregonEugeneUSA
  3. 3.Mitchell Cancer InstituteUniversity of South AlabamaMobileUSA
  4. 4.Department of Cell Biology and NeuroscienceUniversity of South AlabamaMobileUSA

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