Title |
OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data
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Published in |
Journal of Biomedical Semantics, May 2016
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DOI | 10.1186/s13326-016-0064-2 |
Pubmed ID | |
Authors |
Jingshan Huang, Fernando Gutierrez, Harrison J. Strachan, Dejing Dou, Weili Huang, Barry Smith, Judith A. Blake, Karen Eilbeck, Darren A. Natale, Yu Lin, Bin Wu, Nisansa de Silva, Xiaowei Wang, Zixing Liu, Glen M. Borchert, Ming Tan, Alan Ruttenberg |
Abstract |
As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Spain | 1 | 2% |
South Africa | 1 | 2% |
Unknown | 45 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 13% |
Researcher | 5 | 11% |
Student > Bachelor | 4 | 9% |
Student > Ph. D. Student | 4 | 9% |
Student > Doctoral Student | 3 | 6% |
Other | 10 | 21% |
Unknown | 15 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 12 | 26% |
Agricultural and Biological Sciences | 8 | 17% |
Biochemistry, Genetics and Molecular Biology | 4 | 9% |
Engineering | 2 | 4% |
Philosophy | 1 | 2% |
Other | 5 | 11% |
Unknown | 15 | 32% |