• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.47-53
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• 2017

In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Molecules and Cells
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• v.45 no.5
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• pp.306-316
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• 2022

Chronic stress contributes to the risk of developing depression; the habenula, a nucleus in epithalamus, is associated with many neuropsychiatric disorders. Using genome-wide gene expression analysis, we analyzed the transcriptome of the habenula in rats exposed to chronic restraint stress for 14 days. We identified 379 differentially expressed genes (DEGs) that were affected by chronic stress. These genes were enriched in neuroactive ligand-receptor interaction, the cAMP (cyclic adenosine monophosphate) signaling pathway, circadian entrainment, and synaptic signaling from the Kyoto Encyclopedia of Genes and Genomes pathway analysis and responded to corticosteroids, positive regulation of lipid transport, anterograde trans-synaptic signaling, and chemical synapse transmission from the Gene Ontology analysis. Based on protein-protein interaction network analysis of the DEGs, we identified neuroactive ligand-receptor interactions, circadian entrainment, and cholinergic synapse-related subclusters. Additionally, cell type and habenular regional expression of DEGs, evaluated using a recently published single-cell RNA sequencing study (GSE137478), strongly suggest that DEGs related to neuroactive ligand-receptor interaction and trans-synaptic signaling are highly enriched in medial habenular neurons. Taken together, our findings provide a valuable set of molecular targets that may play important roles in mediating the habenular response to stress and the onset of chronic stress-induced depressive behaviors.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.246-251
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• 2006

마이크로어레이 실험은 수 천에서 수 만개의 유전자 발현 결과를 동시에 측정할 수 있어 질병의 발현 형질 분류 등에 유용하게 이용되고 있다. 그러나 마이크로어레이 실험은 동일한 플랫폼의 실험이라 할지라도 환경 등에 따라 그 실험 결과에 차이가 나는 등 오차를 항상 포함하고 있다. 또한 마이크로어레이 실험은 아직 고가의 실험으로 분류되어 다수의 샘플에 대한 반복 실험 결과를 얻기 어려운 상황이다. 따라서 이종의 플랫폼, 데이터 포맷, 정규화 기법 등이 서로 다른 데이터를 효율적으로 통합하여 유용한 정보를 추출하는 새로운 방식의 개발이 필요하다. 본 논문은 이와 같은 문제를 해결하기 위한 기초 단계 연구 결과이다. 마이크로어레이 실험 데이터로부터 통계적 방법을 이용하여 유의(informative) 유전자를 추출하고 유전자 온톨로지(Gene Ontology : GO)와의 연계를 통하여 유전자 정보의 기능적 분류 결과를 사용자에게 제공하는 유전자 기능 분석 시스템의 설계 및 구현 방안을 보인다. 본 시스템의 실험방법에서는 3-Fold Filtering 기법을 통하여 발현 차가 큰 유전자를 추출하고, t-검정 기법에 의하여 이들 유전자를 순위화 하였으며, 이 중 상위 100개의 유전자를 유의 유전자로 추출하였다. 다음, 이 들 유의 유전자의 t-검정 값을 GO의 유전자 기능을 나타내는 해당 텀 (term)에 가중치로 부과하여 각 유전자들과 기능적으로 연관성이 높은 텀들을 추출한다. 또한 본 연구의 유효성을 검증하기 위하여 본 시스템에 의한 마이크로어레이 데이터 분석 결과를 전문가에 의한 유전자 기능 분석 결과와 비교한다.투명성 있는 서비스를 제공하고 높은 신뢰성과 안정성이 확보될 수 있도록 구성하고자 한다. Query 수행을 여러 서버로 분산처리하게 함으로써 성능에 대한 신뢰성을 향상 시킬 수 있는 Load Balancing System을 제안한다.할 때 가장 효과적인 라우팅 프로토콜이라고 할 수 있다.iRNA 상의 의존관계를 분석할 수 있었다.수안보 등 지역에서 나타난다 이러한 이상대 주변에는 대개 온천이 발달되어 있었거나 새로 개발되어 있는 곳이다. 온천에 이용하고 있는 시추공의 자료는 배제하였으나 온천이응으로 직접적으로 영향을 받지 않은 시추공의 자료는 사용하였다 이러한 온천 주변 지역이라 하더라도 실제는 온천의 pumping 으로 인한 대류현상으로 주변 일대의 온도를 올려놓았기 때문에 비교적 높은 지열류량 값을 보인다. 한편 한반도 남동부 일대는 이번 추가된 자료에 의해 새로운 지열류량 분포 변화가 나타났다 강원 북부 오색온천지역 부근에서 높은 지열류량 분포를 보이며 또한 우리나라 대단층 중의 하나인 양산단층과 같은 방향으로 발달한 밀양단층, 모량단층, 동래단층 등 주변부로 NNE-SSW 방향의 지열류량 이상대가 발달한다. 이것으로 볼 때 지열류량은 지질구조와 무관하지 않음을 파악할 수 있다. 특히 이러한 단층대 주변은 지열수의 순환이 깊은 심도까지 가능하므로 이러한 대류현상으로 지표부근까지 높은 지온 전달이 되어 나타나는 것으로 판단된다.의 안정된 방사성표지효율을 보였다. $^{99m}Tc$-transferrin을 이용한 감염영상을 성공적으로 얻을 수 있었으며, $^{67}Ga$-citrate

• Molecules and Cells
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• v.28 no.6
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• pp.529-536
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• 2009

Genome sequencing of the pig is being accelerated because of its importance as an evolutionary and biomedical model animal as well as a major livestock animal. However, information on expressed porcine genes is insufficient to allow annotation and use of the genomic information. A series of expressed sequence tags of 5' ends of five full-length enriched cDNA libraries (SUSFLECKs) were functionally characterized. SUSFLECKs were constructed from porcine abdominal fat, induced fat cells, loin muscle, liver, and pituitary gland, and were composed of non-normalized and normalized libraries. A total of 55,658 ESTs that were sequenced once from the 5′ ends of clones were produced and assembled into 17,684 unique sequences with 7,736 contigs and 9,948 singletons. In Gene Ontology analysis, two significant biological process leaf nodes were found: gluconeogenesis and translation elongation. In functional domain analysis based on the Pfam database, the beta transducin repeat domain of WD40 protein was the most frequently occurring domain. Twelve genes, including SLC25A6, EEF1G, EEF1A1, COX1, ACTA1, SLA, and ANXA2, were significantly more abundant in fat tissues than in loin muscle, liver, and pituitary gland in the SUSFLECKs. These characteristics of SUSFLECKs determined by EST analysis can provide important insight to discover the functional pathways in gene networks and to expand our understanding of energy metabolism in the pig.

• Journal of Life Science
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• v.22 no.11
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• pp.1552-1557
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• 2012

It has been reported that pipernonaline isolated from Piper longum Linn. has a wide biochemical and pharmacological effect, including antitumor activity in prostate cancer PC-3 cells. However, its mechanism and expression pattern of many genes involved in biological functions are not clearly understood. To perform the gene expression study in PC-3 cells treated with pipernonaline, a cDNA microarray chip composed of 44,000 human cDNA probes was used. As a result, cell cycle-related genes, apoptosis-related genes, and cell proliferation/growth-related genes have been identified in gene ontology of the DAVID database. These results suggest that pipernonaline has antitumor activity by regulating the expression pattern of genes involved in biological signaling pathway in prostate cancer PC-3 cells. Further, additional analysis of these microarray data can be a useful tool to identify the mechanism and discovery of novel genes in cancer therapy.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.529-535
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• 2015

Biological networks have been handled with the static concept. However, life phenomena in cells occur depending on the cellular state and the external environment, and only a few proteins and their interactions are selectively activated. Therefore, we should adopt the dynamic network concept that the structure of a biological network varies along the flow of time. This concept is effective to analyze the progressive transition of the disease. In this paper, we applied the proposed method to Alzheimer's disease to analyze the structural and functional characteristics of the disease network. Using gene expression data and protein-protein interaction data, we constructed the sub-networks in accordance with the progress of disease (normal, early, middle and late). Based on this, we analyzed structural properties of the network. Furthermore, we found module structures in the network to analyze the functional properties of the sub-networks using the gene ontology analysis (GO). As a result, it was shown that the functional characteristics of the dynamics network is well compatible with the stage of the disease which shows that it can be used to describe important biological events of the disease. Via the proposed approach, it is possible to observe the molecular network change involved in the disease progression which is not generally investigated, and to understand the pathogenesis and progression mechanism of the disease at a molecular level.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.598-606
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• 2013

Anther is the major organ of flower in responsible to reproduction and outward appearance. From anther-specific cDNA library of Lilium Oriental Hybrid 'Acapulco', 2000 expressed sequence tags were selected randomly. Differential slot blot analysis with cDNA probes from the anther and leaf was used to get anther-expressed clone and 570 non-redundant ESTs were obtained and sequenced. Compared to the GenBank database using BLASTX algorithm, 191 clones showed significant similarity but others (66.5%) did not measured to known sequence. Functional categories according to gene ontology (GO) annotation included sequence representing a significant portion of protein in cell and cell part respectively. A transcriptional analysis at 7 different organs and developmental stage was performed using northern blot with thirty ESTs as putative anther specific gene. This report suggest that selection of anther expressed clone using differential slot blot was considered as very effective tool and our current study can provide fundamental information on the lily anther including pollen furthermore.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.284-288
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• 2009

With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

• Journal of Environmental Science International
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• v.24 no.5
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• pp.623-631
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• 2015

Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). This study, the mRNA expression profiles provide insight into the mechanism of action of cadmium in Fleshy shrimp (Fenneropenaeus chinensis). The ability of genomic technologies was contributed decisively to development of new molecular biomarkers and to the determination of new possible gene targets. Also, it can be approach for monitoring of trace metal using oligo-chip microarray-based in potential model marine user level organisms. 15K oligo-chip for F. chinensis that include mostly unique sets of genes from cDNA sequences was developed. A total of 13,971 spots (1,181 mRNAs up- regulated and 996 down regulated) were identified to be significantly expressed on microarray by hierarchical clustering of genes after exposure to cadmium for different conditions (Cd24-5000 and Cd48-1000). Most of the changes of mRNA expression were observed at the long time and low concentration exposure of Cd48-1000. But, gene ontology analysis (GO annotation) were no significant different between experiments groups. It was observed that mRNA expression of main genes involved in metabolism, cell component, molecular binding and catalytic function. It was suggested that cadmium inhibited metabolism and growth of F. chinensis.