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

• Published in: Pharmaceutical research Vol. 28; no. 12; pp. 3101 - 3104
• Main Authors: Huang, Jingshan, Townsend, Christopher, Dou, Dejing, Liu, Haishan, Tan, Ming
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.12.2011; Springer Nature B.V
• Subjects: Biochemistry; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Cancer; Commentary; Gene therapy; Humans; Knowledge; Knowledge Bases; Medical Law; MicroRNAs - genetics; Neoplasms - genetics; Pharmaceutical sciences; Pharmacology/Toxicology; Pharmacy; Ribonucleic acid; RNA; Software; User-Computer Interface; knowledge base; microRNA (miRNA) target; human cancer; knowledge acquisition; ontology
• ISSN: 0724-8741; 1573-904X; 1573-904X
• DOI: 10.1007/s11095-011-0573-8

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.