OMIT: Dynamic, Semi-Automated Ontology Development for the microRNA Domain

Abstract

As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

Effectiveness and Usability of Bioinformatics Tools to Analyze Pathways Associated with miRNA Expression

“…A key issue in assessing miRNA-related databases is the integration of disseminated information across multiple databases that is often in different formats, 16 leading to a lack of standardization in miRNA nomenclature. 17 While existing tools integrate this information differently, one component of our comparison is how effectively bioinformatics tools accomplish this integration. A third methodological challenge is the inconsistent versions of databases for each analysis tool.…”

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

“…Compared with the previous versions [ 12 – 17 ], important changes in the current version OMIT ontology are summarized as follows. As discussed earlier in “ Modularized ontology design ” Section, we have followed a modularized ontology design in this new version, which will significantly further facilitate the ontology maintenance and update.…”

“…In previous research [ 12 – 17 ], we investigated the construction of an application ontology for the miRNA field, named Ontology for MIcroRNA Target (OMIT), the first ontology to formally encode miRNA domain knowledge. By providing a standardized metadata model to establish miRNA data connections among heterogeneous sources, the OMIT is able to fill two gaps: the lack of common data elements and the lack of data exchange standards for miRNA research, especially with regard to miRNA-target interactions.…”

The role of ontologies in biological and biomedical research: a functional perspective

“…There are now sufficient stable ontologies to permit routine reuse of classes from multiple ontologies in automated or semiautomated ontology construction algorithms [ 109 ]. With increasing size and number of ontologies, the ability to modularize ontologies to generate application-specific ‘views’ while maintaining interoperability with data sets in a domain that are annotated with another module of the same ontology will become essential.…”