• Interdisciplinary Bio Central
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• 제5권1호
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• pp.1.1-1.8
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• 2013

High quality publicly-available transcriptomic data representing relationships in gene expression across a diverse set of biological conditions is used as a context network to explore transcriptomics of the CNS. The context network, 18367Hu-matrix, contains pairwise Pearson correlations for 22,215 human genes across18,637 human tissue samples1. To do this, we compute a network derived from biological samples from CNS cells and tissues, calculate clusters of co-expressed genes from this network, and compare the significance of these to clusters derived from the larger 18367Hu-matrix network. Sorting and visualization uses the publicly available software, MetaOmGraph (http://www.metnetdb.org/MetNet_MetaOm-Graph.htm). This identifies genes that characterize particular disease conditions. Specifically, differences in gene expression within and between two designations of glial cancer, astrocytoma and glioblastoma, are evaluated in the context of the broader network. Such gene groups, which we term outlier-networks, tease out abnormally expressed genes and the samples in which this expression occurs. This approach distinguishes 48 subnetworks of outlier genes associated with astrocytoma and glioblastoma. As a case study, we investigate the relationships among the genes of a small astrocytoma-only subnetwork. This astrocytoma-only subnetwork consists of SVEP1, IGF1, CHRNA3, and SPAG6. All of these genes are highly coexpressed in a single sample of anaplastic astrocytoma tumor (grade III) and a sample of juvenile pilocytic astrocytoma. Three of these genes are also associated with nicotine. This data lead us to formulate a testable hypothesis that this astrocytoma outlier-network provides a link between some gliomas/astrocytomas and nicotine.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• 한국과학교육학회지
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• 제29권3호
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• pp.348-358
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• 2009

The purpose of this study was to investigate brain activation pattern and functional connectivity network during experimental design on the biological phenomena. Twenty six right-handed healthy science teachers volunteered to be in the present study. To investigate participants' brain activities during the tasks, 3.0T fMRI system with the block experimental-design was used to measure BOLD signals of their brain and SPM2 software package was applied to analyze the acquired initial image data from the fMRI system. According to the analyzed data, superior, middle and inferior frontal gyrus, superior and inferior parietal lobule, fusiform gyrus, lingual gyrus, and bilateral cerebellum were significantly activated during participants' carrying-out experimental design. The network model was consisting of six nodes (ROIs) and its six connections. These results suggested the notion that the activation and connections of these regions mean that experimental design process couldn't succeed just a memory retrieval process. These results enable the scientific experimental design process to be examined from the cognitive neuroscience perspective, and may be used as a basis for developing a teaching-learning program for scientific experimental design such as brain-based science education curriculum.

• BMB Reports
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• 제33권5호
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• pp.370-378
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• 2000

Incubation of purified laminin1-nidogen1 complexes with $[{\gamma}-^{32}P]-ATP$ in the presence of the catalytic subunit of the protein kinase A (cAMP-dependent protein kinase) resulted in the phosphorylation of the alpha chain of laminin-1 and of the nidogen-1 molecule. Aminoacid electrophoresis indicated that phosphate was incorporated on serine residues. The phosphorylation effect of laminin-1 on the process of self assembly was studied by turbidometry. In these experiments, the phosphorylated laminin-1 showed a reduced maximal aggregation capacity in comparison to the non-phosphorylated molecule. Examination of the laminin-1 network under the electron microscope showed that the phosphorylated sample formed mainly linear extended oligomers, in contrast to controls that formed large and dense multimeric aggregates. Heparin binding on phosphorylated laminin-1 in comparison to controls was also tested using solid-phase binding assays. The results indicated an enhanced heparin binding to the phosphorylated protein. The results of this study indicate that laminin1-nidogen1 is a substrate for protein kinase A in vitro. This phosphorylation had an obvious influence on the lamininl-nidogen1 network formation and the heparin binding capacity of this molecule. However, further studies are needed to investigate whether or not this phenomenon could play a role in the formation of the structure of basement membranes in vivo.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2014년도 춘계 종합학술대회 논문집
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• pp.233-234
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• 2014

• Journal of Ginseng Research
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• 제47권1호
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• pp.54-64
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• 2023

Background: Panax ginseng Meyer (P. ginseng) is a traditional natural/herbal medicine. The amelioration on inflammatory bowel disease (IBD) activity rely mainly on its main active ingredients that are referred to as ginsenosides. However, the current literature on gut microbiota, gut microbiota-host co-metabolites, and systems pharmacology has no studies investigating the effects of ginsenoside on IBD. Methods: The present study was aimed to investigate the role of ginsenosides and the possible underlying mechanisms in the treatment of IBD in an acetic acid-induced rat model by integrating metagenomics, metabolomics, and complex biological networks analysis. In the study ten ginsenosides in the ginsenoside fraction (GS) were identified using Q-Orbitrap LC-MS. Results: The results demonstrated the improvement effect of GS on IBD and the regulation effect of ginsenosides on gut microbiota and its co-metabolites. It was revealed that 7 endogenous metabolites, including acetic acid, butyric acid, citric acid, tryptophan, histidine, alanine, and glutathione, could be utilized as significant biomarkers of GS in the treatment of IBD. Furthermore, the biological network studies revealed EGFR, STAT3, and AKT1, which belong mainly to the glycolysis and pentose phosphate pathways, as the potential targets for GS for intervening in IBD. Conclusion: These findings indicated that the combination of genomics, metabolomics, and biological network analysis could assist in elucidating the possible mechanism underlying the role of ginsenosides in alleviating inflammatory bowel disease and thereby reveal the pathological process of ginsenosides in IBD treatment through the regulation of the disordered host-flora co-metabolism pathway.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2014년도 추계학술발표대회
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• pp.849-852
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• 2014

Reverse engineering of gene regulatory network is a challenging task in computational biology. To detect a regulatory relationship among genes from time series data is called reverse engineering. Reverse engineering helps to discover the architecture of the underlying gene regulatory network. Besides, it insights into the disease process, biological process and drug discovery. There are many statistical approaches available for reverse engineering of gene regulatory network. In our paper, we propose pairwise mutual information for the reverse engineering of a gene regulatory network from time series data. Firstly, we create random boolean networks by the well-known $Erd{\ddot{o}}s-R{\acute{e}}nyi$ model. Secondly, we generate artificial time series data from that network. Then, we calculate pairwise mutual information for predicting the network. We implement of our system on java platform. To visualize the random boolean network graphically we use cytoscape plugins 2.8.0.

• 한국고분자학회:학술대회논문집
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• 한국고분자학회 2006년도 IUPAC International Symposium on Advanced Polymers for Emerging Technologies
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• pp.297-297
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• 2006

Recently columnar liquid crystals have been studied due to their possible application to organic conducting materials. Supramolecular columnar liquid crystals consist of mesogenic unit which can aggregate into discs that will make up the columns which associate to form a two-dimensional network. In this study, we prepared supramolecular columnar liquid crystals containing hydrogen bonding between carboxylic acid and, pyridine moieties. Thermal and structural properties of prepared complexe were investigated, and it exhibited hexagonal columnar structure ($Col_{h}$) at room temperature.

• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.343-350
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• 1989

A new algorithm classifying ECG Arrhythmia signals using Back-propagation network is proposed. The base-line of ECG signal is detected by high pass filter and probability density function then input data are normalized for learning and classifying. In addition, ECG data are scanned to classify Arrhythmia signal which is hard to find R-wave. A two-layer perceptron with one hidden layer along with error back-propagation learning rule is utilized as an artificial neural network. The proposed algorithm shows outstanding performance under circumstances of amplitude variation, baseline wander and noise contamination.

• 한국유기농업학회지
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• 제19권spc호
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• pp.111-114
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• 2011

Construction of the Asian Network for Sustainable Organic Farming Technology (ANSOFT) will be cooperatively administered by the public researchers in 12 Asian member countries from 2010 to 2012. ANSOFT will bring forward multiple reports, which will be constantly renewed by the member countries, regarding environmental issues, plant and landscape protection techniques, regulations and policies of each country's government on an organic agriculture, and natural resources such as organic seeds and biological agents.