ABSTRACT
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.
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ACKNOWLEDGMENTS
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.
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Huang, J., Townsend, C., Dou, D. et al. OMIT: A Domain-Specific Knowledge Base for MicroRNA Target Prediction. Pharm Res 28, 3101–3104 (2011). https://doi.org/10.1007/s11095-011-0573-8
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DOI: https://doi.org/10.1007/s11095-011-0573-8