• 전자공학회논문지CI
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• 제45권4호
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• pp.19-26
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• 2008

Gene set enrichment analysis (GSEA)는 두 개의 클래스를 가지는 마이크로어레이 실험 데이터 분석을 위해 생물학적 특징을 기반으로 구성된 다양한 유전자-집합 중에서 두 클래스의 발현값들이 통계적으로 중요한 차이를 나타내는 유의한 유전자-집합을 추출하기 위한 분석 방법이다. 특히, 유전자에 대한 다양한 생물학적인 정보를 지닌 유전자 주석 데이터베이스(Cytogenetic Band, KEGG pathway, Gene Ontology 등)를 이용하여 마이크로어레이 실험에 사용된 전체 유전자 중 특정 기능을 가지는 유전자들을 그룹화하여 다양한 유전자-집합을 발굴하고, 각 유전자-집합 내에서 두 클래스간에 발현값의 차이를 참조하여 유의한 유전자들을 결정하여, 이를 기반으로 통계적으로 유의한 유전자-집합들을 최종 검출하는 방법이다. 본 논문에서는 GSEA 분석 과정에서 현재 주로 사용되고 있는 signal-to-noise ratio 기반 유전자 서열화(gene ranking) 방법 대신에, Fisher criterion을 이용한 유전자 서열화 방법을 적용함으로써 기존의 GSEA 방법에서 추출하지 못한 생물학적으로 의미 있는 새로운 유의 유전자-집합을 추출하는 방법을 제안하고자 한다. 또한, 제안한 방법의 성능을 고찰하기 위하여 공개된 Leukemia 관련 마이크로어레이 실험 데이터 분석에 적용하였으며, 기존의 알려진 결과와 비교 분석함으로써 제안한 방법의 유용성을 검증하고자 하였다.

• Molecules and Cells
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• 제42권8호
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• pp.579-588
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• 2019

Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea.

• Genomics & Informatics
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• 제21권4호
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• pp.45.1-45.11
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• 2023

Nonalcoholic fatty liver disease (NAFLD) is a common type of chronic liver disease, with severity levels ranging from nonalcoholic fatty liver to nonalcoholic steatohepatitis (NASH). The extent of liver fibrosis indicates the severity of NASH and the risk of liver cancer. However, the mechanism underlying NASH development, which is important for early screening and intervention, remains unclear. Weighted gene co-expression network analysis (WGCNA) is a useful method for identifying hub genes and screening specific targets for diseases. In this study, we utilized an mRNA dataset of the liver tissues of patients with NASH and conducted WGCNA for various stages of liver fibrosis. Subsequently, we employed two additional mRNA datasets for validation purposes. Gene set enrichment analysis (GSEA) was conducted to analyze gene function enrichment. Through WGCNA and subsequent analyses, complemented by validation using two additional datasets, we identified five genes (BICC1, C7, EFEMP1, LUM, and STMN2) as hub genes. GSEA analysis indicated that gene sets associated with liver metabolism and cholesterol homeostasis were uniformly downregulated. BICC1, C7, EFEMP1, LUM, and STMN2 were identified as hub genes of NASH, and were all related to liver metabolism, NAFLD, NASH, and related diseases. These hub genes might serve as potential targets for the early screening and treatment of NASH.

• Genomics & Informatics
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• 제5권3호
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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.

• Biomolecules & Therapeutics
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• 제30권1호
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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.

• BMB Reports
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• 제45권2호
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• pp.120-125
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• 2012

We have developed a biologist-friendly, Java GUI application (GoBean) for GO term enrichment analysis. It was designed to be a comprehensive and flexible GUI tool for GO term enrichment analysis, combining the merits of other programs and incorporating extensive graphic exploration of enrichment results. An intuitive user interface with multiple panels allows for extensive visual scrutiny of analysis results. The program includes many essential and useful features, such as enrichment analysis algorithms, multiple test correction methods, and versatile filtering of enriched GO terms for more focused analyses. A unique graphic interface reflecting the GO tree structure was devised to facilitate comparisons of multiple GO analysis results, which can provide valuable insights for biological interpretation. Additional features to enhance user convenience include built in ID conversion, evidence code-based gene-GO association filtering, set operations of gene lists and enriched GO terms, and user -provided data files. It is available at http://neon.gachon.ac.kr/GoBean/.

• Genomics & Informatics
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• 제18권4호
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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.

• 한국수정란이식학회지
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• 제33권4호
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• pp.245-254
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• 2018

Pigs are considered as optimal donor animal for the successful xenotransplantation. To increase the possibility of clinical application, genetic modification to increase compatibility with human is an important and essential process. Genetic modification technique has been developed and improved to produce genetically modified pigs rapidly. CRISPR/Cas9 system is widely used in various fields including the production of transgenic animals and also can be enable multiple gene modifications. In this study, we developed new gene targeting vector and enrichment system for the rapid and efficient selection of genetically modified cells. We conducted co-transfection with two targeting vectors for simultaneous inactivation of two genes and enrichment of the genetically modified cells using MACS. After this efficient enrichment, genotypic analysis of each colony showed that colonies which have genetic modifications on both genes were confirmed with high efficiency. Somatic cell nuclear transfer was conducted with established donor cells and genetically modified pigs were successfully produced. Genotypic and phenotypic analysis of generated pigs showed identical genotypes with donor cells and no surface expression of ${\alpha}$-Gal and HD antigens. Furthermore, functional analysis using pooled human serum revealed dramatically reduction of human natural antibody (IgG and IgM) binding level and natural antibody-mediated cytotoxicity. In conclusion, the constructed vector and enrichment system using MACS used in this study is efficient and useful to generate genetically modified donor cells with multiple genetic alterations and lead to an efficient production of genetically modified pigs.

• Genomics & Informatics
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• 제15권2호
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• pp.56-64
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• 2017

We have previously reported that NS-398, a cyclooxygenase-2 (COX-2)-selective inhibitor, inhibited replicative cellular senescence in human dermal fibroblasts and skin aging in hairless mice. In contrast, celecoxib, another COX-2-selective inhibitor, and aspirin, a non-selective COX inhibitor, accelerated the senescence and aging. To figure out causal factors for the senescence-modulating effect of the inhibitors, we here performed cDNA microarray experiment and subsequent Gene Set Enrichment Analysis. The data showed that several senescence-related gene sets were regulated by the inhibitor treatment. NS-398 up-regulated gene sets involved in the tumor necrosis factor ${\beta}$ receptor pathway and the fructose and mannose metabolism, whereas it down-regulated a gene set involved in protein secretion. Celecoxib up-regulated gene sets involved in G2M checkpoint and E2F targets. Aspirin up-regulated the gene set involved in protein secretion, and down-regulated gene sets involved in RNA transcription. These results suggest that COX inhibitors modulate cellular senescence by different mechanisms and will provide useful information to understand senescence-modulating mechanisms of COX inhibitors.

• Communications for Statistical Applications and Methods
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• 제16권3호
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• pp.397-408
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• 2009

마이크로어레이 기술은 수만 개 유전자의 발현 패턴을 동시에 관찰하는 것을 가능하게 하였고, 이들을 하나씩 검정하여 찾아낸 특이발현 현상을 보이는 유전자를 중심으로 질병의 진단, 치료법 정립과 신약 개발을 위한 기본 정보를 확립하였다. 그러나 개별 유전자분석의 여러 문제점이 발견되면서 유전자들을 생물학적 대사경로나 염색체 위치가 같은 것끼리 묶은 집단을 분석하여 질병의 발생이나 생존에 영향을 미치는 집단을 찾는 방법이 제시되었다. 이러한 유전자 집단의 유의성에 대한 연구는 2002년에 MIT에서 비롯되어 GSEA, SAM-GS와 중심극한 정리의 개념을 이용한 모수적 방법인 PAGE 등이 사용되고 있다. 본 논문에서는 이들 통계량의 구조적 한계를 극복하고 계산이 간단한 새로운 모수적 방법을 제안하고 자료 분석을 통하여 효율성을 보였다.