caa a22 4500 445312459 CHVBK 20180317142635.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s11095-011-0573-8 doi (NATIONALLICENCE)springer-10.1007/s11095-011-0573-8 OMIT: A Domain-Specific Knowledge Base for MicroRNA Target Prediction [Elektronische Daten] [Jingshan Huang, Christopher Townsend, Dejing Dou, Haishan Liu, Ming Tan] 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. Springer Science+Business Media, LLC, 2011 human cancer nationallicence knowledge acquisition nationallicence knowledge base nationallicence microRNA (miRNA) target nationallicence ontology nationallicence Huang Jingshan School of Computer and Information Sciences, University of South Alabama, 307 University Blvd. N, Mobile, Alabama, USA aut Townsend Christopher School of Computer and Information Sciences, University of South Alabama, 307 University Blvd. N, Mobile, Alabama, USA aut Dou Dejing Department of Computer and Information Science, University of Oregon, Eugene, Oregon, USA aut Liu Haishan Department of Computer and Information Science, University of Oregon, Eugene, Oregon, USA aut Tan Ming Mitchell Cancer Institute, University of South Alabama, Mobile, Alabama, USA aut Pharmaceutical Research Springer US; http://www.springer-ny.com 28/12(2011-12-01), 3101-3104 0724-8741 28:12<3101 2011 28 11095 https://doi.org/10.1007/s11095-011-0573-8 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11095-011-0573-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Huang Jingshan School of Computer and Information Sciences, University of South Alabama, 307 University Blvd. N, Mobile, Alabama, USA aut NATIONALLICENCE 700 1- Townsend Christopher School of Computer and Information Sciences, University of South Alabama, 307 University Blvd. N, Mobile, Alabama, USA aut NATIONALLICENCE 700 1- Dou Dejing Department of Computer and Information Science, University of Oregon, Eugene, Oregon, USA aut NATIONALLICENCE 700 1- Liu Haishan Department of Computer and Information Science, University of Oregon, Eugene, Oregon, USA aut NATIONALLICENCE 700 1- Tan Ming Mitchell Cancer Institute, University of South Alabama, Mobile, Alabama, USA aut NATIONALLICENCE 773 0- Pharmaceutical Research Springer US; http://www.springer-ny.com 28/12(2011-12-01), 3101-3104 0724-8741 28:12<3101 2011 28 11095 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer