• Genomics & Informatics
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• v.3 no.2
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• pp.47-51
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• 2005

Molecular mechanisms of biological processes are typically represented as 'pathways' that have a graph­analogical network structure. However, due to the diversity of topics that pathways cover, their constituent biological entities are highly diverse and the semantics is embedded implicitly. The kinds of interactions that connect biological entities are likewise diverse. Consequently, how to model or process pathway data is not a trivial issue. In this review article, we give an overview of the challenges in pathway database development by taking the INOH project as an example.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.388-391
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• 2005

The Protein Structural and Functional Conservation need a common language for data definition. With the help of common language provided by Protein Ontology the high level of sequence and functional conservation can be extended to all organisms with the likelihood that proteins that carry out core biological processes will again be probable orthologues. The structural and functional conservation in these proteins presents both opportunities and challenges. The main opportunity lies in the possibility of automated transfer of protein data annotations from experimentally traceable model organisms to a less traceable organism based on protein sequence similarity. Such information can be used to improve human health or agriculture. The challenge lies in using a common language to transfer protein data annotations among different species of organisms. First step in achieving this huge challenge is producing a structured, precisely defined common vocabulary using Protein Ontology. The Protein Ontology described in this paper covers the sequence, structure and biological roles of Protein Complexes in any organism.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.301-305
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• 2002

Bioinformatics can beexplained as the science of developing algorithms, applicatiou tools, and computer databases and so on, for the purpose of supporting and enhancing biological research. Bioinformatic information systems (BIS) typically handle large data sets and the amount of the data goes up exponentially. Another impediment to easy extraction and retrieval of genomic data in BIS is the need to access different sites for similar information. Recently. there has been some attempts to integrate bioinformatics data in the World Wide Web (WWW) among the bioinformatics community by the internet computing technology. However, the work to integrate bioinformatics data on a universal platform has some problems because of the lack of standard, terminologies, semantics, and ontologies about bioinformatics. In this paper, an XML-based BIS architecture is proposed as an integrated BIS framework. The XML and related technologies allow the creation of meaningful information tags to exchange data between various databases as a standard format, and to create more simple interfaces. This integrated BIS framework has bioinformatic architectural components which is used in the Corporate Information Factory (CIF) method.

• Interdisciplinary Bio Central
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• v.3 no.2
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• pp.7.1-7.6
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• 2011

Background: Published manuscripts are the main source of biological knowledge. Since the manual examination is almost impossible due to the huge volume of literature data (approximately 19 million abstracts in PubMed), intelligent text mining systems are of great utility for knowledge discovery. However, most of current text mining tools have limited applicability because of i) providing abstract-based search rather than sentence-based search, ii) improper use or lack of ontology terms, iii) the design to be used for specific subjects, or iv) slow response time that hampers web services and real time applications. Results: We introduce an advanced text mining system called PubMine that supports intelligent knowledge discovery based on diverse bio-ontologies. PubMine improves query accuracy and flexibility with advanced search capabilities of fuzzy search, wildcard search, proximity search, range search, and the Boolean combinations. Furthermore, PubMine allows users to extract multi-dimensional relationships between genes, diseases, and chemical compounds by using OLAP (On-Line Analytical Processing) techniques. The HUGO gene symbols and the MeSH ontology for diseases, chemical compounds, and anatomy have been included in the current version of PubMine, which is freely available at http://pubmine.kobic.re.kr. Conclusions: PubMine is a unique bio-text mining system that provides flexible searches and analysis of biological entity relationships. We believe that PubMine would serve as a key bioinformatics utility due to its rapid response to enable web services for community and to the flexibility to accommodate general ontology.

• Genomics & Informatics
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• v.18 no.2
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• pp.23.1-23.6
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• 2020

The Human Phenotype Ontology (HPO) is the de facto standard ontology to describe human phenotypes in detail, and it is actively used, particularly in the field of rare disease diagnoses. For clinicians who are not fluent in English, the HPO has been translated into many languages, and there have been four initiatives to develop Japanese translations. At the Biomedical Linked Annotation Hackathon 6 (BLAH6), a rule-based approach was attempted to determine the preferable Japanese translation for each HPO term among the candidates developed by the four approaches. The relationship between the HPO and Mammalian Phenotype translations was also investigated, with the eventual goal of harmonizing the two translations to facilitate phenotype-based comparisons of species in Japanese through cross-species phenotype matching. In order to deal with the increase in the number of HPO terms and the need for manual curation, it would be useful to have a dictionary containing word-by-word correspondences and fixed translation phrases for English word order. These considerations seem applicable to HPO localization into other languages.

• Journal of Environmental Health Sciences
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• v.49 no.4
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• pp.201-209
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• 2023

Background: To describe domain knowledge consistently and precisely, the establishment of a controlled vocabulary, a so-called ontology, is essential. Internationally, the plant ontology (PO) in the ecology field has been developed for the anatomy and developmental stages of plants in English, Spanish, and Japanese, but there is no Korean version of the PO due to a lack of knowledge on standardization for Korean plants. Objectives: We aimed to establish a Korean plant ontology with core PO architectures. Methods: The latest ontology web language (OWL)-formatted raw version of the PO was collected from the PO consortium site. A formal workflow process and OWL file-handing tools for efficient Korean content development were conducted and executed. Results: The macro- and micro-perspective frameworks of the PO were presented by analyzing the upper model and the internal OWL-leveled physical structure, respectively. We developed and validated Korean knowledge content for a total of 1,957 classes included in the PO and transplanted them into an ontology modeling system. Conclusions: A Korean plant ontology was established for international harmonization through improved compatibility and data exchangeability with multilingual environmental and ecological knowledge bases.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.461-472
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• 2005

In this paper, we design and implement a graphical bio-ontology management system based on OWL(Web Ontology Language). It allows domain experts to easily manage sophisticated bio-ontologies in which biological knowledge is encoded. The knowledge can be seamlessly modeled into the ontology by well defined graphical notations, which capture most of subtle semantics inherently existing between biological terms. Our system provides a new construction mechanism, which can determine a considerable part of relationships between terms by their inheritance and inverse-inheritance. For keeping their semantics to be consistent, the mechanism supplies domain experts with information available from relationships being constructed or already constructed. The constructed ontology is basically formatted by OWL, which may benefit from its powerful semantic expressiveness. Additionally, it can be automatically translated into other standard languages without semantic loss, such as RDF/RDFS, DAML+OIL and so on. The main characteristics of our system is that it enables domain experts to delicately model the bio-ontology by the visualized construction mechanisms adopting well-defined graphical notations based on OWL.