• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.19-26
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• 2008

Gene set enrichment analysis (GSEA) is a computational method to identify statistically significant gene sets showing significant differences between two groups of microarray expression profiles and simultaneously uncover their biological meanings in an elegant way by employing gene annotation databases, such as Cytogenetic Band, KEGG pathways, gene ontology, and etc. For the gone set enrichment analysis, all the genes in a given dataset are first ordered by the signal-to-noise ratio between the groups and then further analyses are proceeded. Despite of its impressive results in several previous studies, however, gene ranking by the signal-to-noise ratio makes it difficult to consider highly up-regulated genes and highly down-regulated genes at the same time as the candidates of significant genes, which possibly reflect certain situations incurred in metabolic and signaling pathways. To deal with this problem, in this article, we investigate the gene set enrichment analysis method with Fisher criterion for gene ranking and also evaluate its effects in Leukemia related pathway analyses.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.365-374
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• 2008

In this paper, we propose a model to enrich an ontology by incrementally extending the relations through variations of patterns. In order to generalize initial patterns, combinations of features are considered as candidate patterns. The candidate patterns are used to extract relations from Wikipedia, which are sorted out according to reliability based on corpus frequency. Selected patterns then are used to extract relations, while extracted relations are again used to extend the patterns of the relation. Through making variations of patterns in incremental enrichment process, the range of pattern selection is broaden and refined, which can increase coverage and accuracy of relations extracted. In the experiments with single-feature based pattern models, we observe that the features of lexical, headword, and hypernym provide reliable information, while POS and syntactic features provide general information that is useful for enrichment of relations. Based on observations on the feature types that are appropriate for each syntactic unit type, we propose a pattern model based on the composition of features as our ongoing work.

• Biomolecules & Therapeutics
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• v.30 no.1
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• pp.98-116
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• 2022

The small GTPase RhoA has been studied extensively for its role in actin dynamics. In this study, multiple bioinformatics tools were applied cooperatively to the microarray dataset GSE64714 to explore previously unidentified functions of RhoA. Comparative gene expression analysis revealed 545 differentially expressed genes in RhoA-null cells versus controls. Gene set enrichment analysis (GSEA) was conducted with three gene set collections: (1) the hallmark, (2) the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and (3) the Gene Ontology Biological Process. GSEA results showed that RhoA is related strongly to diverse pathways: cell cycle/growth, DNA repair, metabolism, keratinization, response to fungus, and vesicular transport. These functions were verified by heatmap analysis, KEGG pathway diagramming, and direct acyclic graphing. The use of multiple gene set collections restricted the leakage of information extracted. However, gene sets from individual collections are heterogenous in gene element composition, number, and the contextual meaning embraced in names. Indeed, there was a limit to deriving functions with high accuracy and reliability simply from gene set names. The comparison of multiple gene set collections showed that although the gene sets had similar names, the gene elements were extremely heterogeneous. Thus, the type of collection chosen and the analytical context influence the interpretation of GSEA results. Nonetheless, the analyses of multiple collections made it possible to derive robust and consistent function identifications. This study confirmed several well-described roles of RhoA and revealed less explored functions, suggesting future research directions.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.199-203
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• 2023

In recent decades, the growth of communication technology has resulted in an explosion of data-related information. Ontology perception is being used as a growing requirement to integrate data and unique functionalities. Ontologies are not only critical for transforming the traditional web into the semantic web but also for the development of intelligent applications that use semantic enrichment and machine learning to transform data into smart data. To address these unclear facts, several researchers have been focused on expanding ontologies and semantic web technologies. Due to the lack of clear-cut limitations, ontologies would not suffice to deliver uncertain information among domain ideas, conceptual formalism supplied by traditional. To deal with this ambiguity, it is suggested that fuzzy ontologies should be used. It employs Ontology to introduce fuzzy logical policies for ambiguous area concepts such as darkness, heat, thickness, creaminess, and so on in a device-readable and compatible format. This survey efforts to provide a brief and conveniently understandable study of the research directions taken in the domain of ontology to deal with fuzzy information; reconcile various definitions observed in scientific literature, and identify some of the domain's future research-challenging scenarios. This work is hoping that this evaluation can be treasured by fuzzy ontology scholars. This paper concludes by the way of reviewing present research and stating research gaps for buddy researchers.

• Journal of Information Science Theory and Practice
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• v.11 no.1
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• pp.61-78
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• 2023

Ontological knowledge modelling of epic texts, though being an established research arena backed by concrete multilingual and multicultural works, still suffers from two key shortcomings. Firstly, all epic ontological models developed till date have been designed following ad-hoc methodologies, most often combining existing general purpose ontology development methodologies. Secondly, none of the ad-hoc methodologies consider the potential reuse of existing epic ontological models for enrichment, if available. This paper presents, as a unified solution to the above shortcomings, the design and development of GOMME - the first dedicated methodology for iterative ontological modelling of epics, potentially extensible to works in different research arenas of digital humanities in general. GOMME is grounded in transdisciplinary foundations of canonical norms for epics, knowledge modelling best practices, application satisfiability norms, and cognitive generative questions. It is also the first methodology (in epic modelling but also in general) to be flexible enough to integrate, in practice, the options of knowledge modelling via reuse or from scratch. The feasibility of GOMME is validated via a first brief implementation of ontological modelling of the Indian epic Mahabharata by reusing an existing ontology. The preliminary results are promising, with the GOMME-produced model being both ontologically thorough and competent performance-wise.

• Genomics & Informatics
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• v.5 no.3
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• pp.133-136
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• 2007

The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.553-555
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• 2004

최근 인터넷의 급속한 성장과 더불어 전자메일(I-Mail)은 의사교환의 필수적인 매체로 사용 되어지고 있다. 그러나 편리하고 비용이 들지 앉는 장정을 이용해 엄청난 양의 스맴 메일이 매일같이 솎아져 오고, 이를 해결하기 위한 다양한 연구들이 제시되어져 왔다. 특히. 문서 분류에 널리 쓰이는 베이지안 분류자(Bayesian classifier)가 가장 널리 이용되어지고 있는데, 정확도와 재현율에서 비교적 우수한 성능을 보이고 있다. 그러나 몇 가지 문제점을 갖고 있는데, 첫째, 사전에 사용자에 의해 스팸. 논스팸 메일에 대한 충분한 학습이 선행되어야 하는 정, 둘째, 필터링을 위한 연산시간이 소요되는 점, 셋째, 필터링의 대상이 되는 메일 본문의 내용이 적을 경우 정확한 필터링이 어렵다는 정 등의 문제점이 있다. 본 논문에서는 마지막 문제점으로 지적된 메일 본문의 내용이 적을 경우 즉, 연산을 위한 특징적인 단어들의 부족으로 정확한 분류가 불가능한 경우의 해결방안으로 온틀로지와 Semantic Enrichment 기법을 이용한 스팸 메일 필터링 시스템을 제안한다. 실험 결과, 제안하는 시스템이 베이지안 분류자를 이용한 분류 시스템보다 정확도에서 4.1%, 재현율에서 10.5%. 그리고 F-measure에서 7.64%의 성능향상을 보였다.

• Genomics & Informatics
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• v.18 no.4
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• pp.39.1-39.8
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• 2020

Alzheimer's disease (AD) is a chronic, progressive brain disorder that slowly destroys affected individuals' memory and reasoning faculties, and consequently, their ability to perform the simplest tasks. This study investigated the hub genes of AD. Proteins interact with other proteins and non-protein molecules, and these interactions play an important role in understanding protein function. Computational methods are useful for understanding biological problems, in particular, network analyses of protein-protein interactions. Through a protein network analysis, we identified the following top 10 hub genes associated with AD: PTGER3, C3AR1, NPY, ADCY2, CXCL12, CCR5, MTNR1A, CNR2, GRM2, and CXCL8. Through gene enrichment, it was identified that most gene functions could be classified as integral to the plasma membrane, G-protein coupled receptor activity, and cell communication under gene ontology, as well as involvement in signal transduction pathways. Based on the convergent functional genomics ranking, the prioritized genes were NPY, CXCL12, CCR5, and CNR2.

• Language and Information
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• v.14 no.1
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• pp.165-196
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• 2010

The primary goal of this paper is to propose methods of enriching two heterogeneous ontologies: Sejong Semantic Classes (SJSC) and KorLexNoun 1.5 (KLN). In order to achieve this goal, this study introduces the pros and cons of two ontologies, and analyzes the error patterns found during the fine-grained manual mapping processes between them. Error patterns can be classified into four types: (1) structural defectives involved in node branching, (2) errors in assigning the semantic classes, (3) deficiency in providing linguistic information, and (4) lack of the lexical units representing specific concepts. According to these error patterns, we propose different solutions in order to correct the node branching defectives and the semantic class assignment, to complement the deficiency of linguistic information, and to increase the number of lexical units suitably allotted to their corresponding concepts. Using the results of this study, we can obtain more enriched ontologies by correcting the defects and errors in each ontology, which will lead to the enhancement of practicality for syntactic and semantic analysis.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.5
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• pp.609-624
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• 2013

The objective of this study was to get a comprehensive understanding of how genes in chicken shell gland modulate eggshell strength at the early stage of active calcification. Four 32-week old of purebred Xianju hens with consistent high or low shell breakage strength were grouped into two pairs. Using Affymetrix Chicken Array, a whole-transcriptome analysis was performed on hen's shell gland at 9 h post oviposition. Gene ontology enrichment analysis for differentially expressed (DE) transcripts was performed using the web-based GOEAST, and the validation of DE-transcripts was tested by qRT-PCR. 1,195 DE-transcripts, corresponding to 941 unique genes were identified in hens with strong eggshell compared to weak shell hens. According to gene ontology annotations, there are 77 DE-transcripts encoding ion transporters and secreted extracellular matrix proteins, and at least 26 DE-transcripts related to carbohydrate metabolism or post-translation glycosylation modification; furthermore, there are 88 signaling DE-transcripts. GO term enrichment analysis suggests that some DE-transcripts mediate reproductive hormones or neurotransmitters to affect eggshell quality through a complex suite of biophysical processes. These results reveal some candidate genes involved with eggshell strength at the early stage of active calcification which may facilitate our understanding of regulating mechanisms of eggshell quality.