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OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data

Overview of attention for article published in Journal of Biomedical Semantics, May 2016
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Title
OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data
Published in
Journal of Biomedical Semantics, May 2016
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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
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%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 May 2023.
All research outputs
#18,349,471
of 23,572,509 outputs
Outputs from Journal of Biomedical Semantics
#286
of 361 outputs
Outputs of similar age
#212,473
of 306,254 outputs
Outputs of similar age from Journal of Biomedical Semantics
#19
of 24 outputs
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So far Altmetric has tracked 361 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.