• Herbal Formula Science
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• v.26 no.3
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• pp.237-250
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• 2018

Objectives : This study is a pharmacological network approach, aimed to identify the potential active compounds contained in Curcumae Radix, and their associated targets, to predict the various bio-reactions involved, and finally to establish the cornerstone for the deep-depth study of the representative mechanisms. Methods : The active compounds of Curcumae Radix have been identified using Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The UniProt database was used to collect each of information of all target proteins associated with the active compounds. To find the bio-metabolic processes associated with each target, the DAVID6.8 Gene Functional classifier tool was used. Compound-Target and Target-Pathway networks were analyzed via Cytoscape 3.40. Results : The target information from 32 potential active compounds of Curcumae Radix was collected through TCMSP analysis. The active compounds interact with 133 target genes engaging in total of 885 biological pathways. The most relevant pathway was the lipid-related metabolism, in which 3 representative active compounds were naringenin, oleic acid, and ${\beta}-sitosterol$. The mostly targeted proteins in the lipid pathway were ApoB, AKT1 and PPAR. Conclusions : The pharmacological network analysis is convenient approach to predict the overall metabolic mechanisms in medicinal herb research, which can reduce the processes of various experimental trial and error and provide key clues that can be used to validate and experimentally verify the core compounds.

• Horticultural Science & Technology
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• v.32 no.3
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• pp.359-365
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• 2014

Oriental pear (Pyrus communis L. cv 'Niitaka') was stored at $0^{\circ}C$ for 5 months and major metabolites involved in blackening of the peel were analyzed by untargeted GC-MS and targeted HPLC methods. In this study, peels of sound and skin-blackened pears were analyzed and compared. Skin-blackened fruit was clearly characterized by a distinctive pattern in changes which included a decrease of malic acid, succinic acid, and ascorbic acid, while an increase of fumaric acid, threonine, and gluconic acid, which indicated both reduced metabolic activity and anti-oxidative capacity of the cells. Chlorogenic acid was a major phenolic compound and the peel of sound fruit showed high levels of free phenolic compounds compared than the peel of skin-blackened fruit which are believed to be related to oxidation of phenolics in skin-blackened tissue. The changes or profiling of major metabolites by targeted or untargeted analysis method could become a useful tool for understanding physiology, disorder mechanism, and identifying metabolic networks connecting primary and secondary metabolism in postharvest research.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.59-60
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• 2000

The past few years have seen a dramatic increase in gene expression data on the basis of DNA microarrays or DNA chips. Going beyond a generic view on the genome, microarray data are able to distinguish between gene populations in different tissues of the same organism and in different states of cells belonging to the same tissue. This affords a cell-wide view of the metabolic and regulatory processes under different conditions, building an effective basis for new diagnoses and therapies of diseases. In this talk we present machine learning techniques for effective mining of DNA microarray data. A brief introduction to the research field of machine learning from the computer science and artificial intelligence point of view is followed by a review of recently-developed learning algorithms applied to the analysis of DNA chip gene expression data. Emphasis is put on graphical models, such as Bayesian networks, latent variable models, and generative topographic mapping. Finally, we report on our own results of applying these learning methods to two important problems: the identification of cell cycle-regulated genes and the discovery of cancer classes by gene expression monitoring. The data sets are provided by the competition CAMDA-2000, the Critical Assessment of Techniques for Microarray Data Mining.

• 한국환경농학회:학술대회논문집
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• 2011.07a
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• pp.196-204
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• 2011

Abiotic stress is the primary cause of crop loss worldwide, reducing average yields for most major crop plants by more than 50%. In addition, future agricultural production and management will encounter multifaceted challenges from global climate change. Therefore, it is necessary to study the molecular response of crop plants to the stresses in order to develop appropriate strategies to sustain food production under adverse environmental conditions. We carried out a large scale proteomic analysis of soybean plants in response to various abiotic stresses, including drought, salinity, waterlogging and their interactions. Proteins were analyzed by two dimensional polyacrylamide gel electrophoresis followed by matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry. The identified proteins are involved in a wide range of cellular functions. In addition to the well known stress-associated proteins, we identified several novel proteins, which were not reported before. In many cases our proteomic data bridges the gap between mRNA and metabolite data. Our studie provides new insights into identification of abiotic stress responsive proteins in soybean, and demonstrates the advantages of proteomic analysis in dissecting metabolic and regulatory networks.

• Horticultural Science & Technology
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• v.33 no.1
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• pp.114-123
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• 2015

Plants can respond and adapt to cold stress through regulation of gene expression in various biochemical and physiological processes. Cold stress triggers decreased rates of metabolism, modification of cell walls, and loss of membrane function. Hence, this study was conducted to construct coexpression networks for time-based expression pattern analysis of genes related to cold stress in Chinese cabbage (Brassica rapa ssp. pekinensis). B. rapa cold stress networks were constructed with 2,030 nodes, 20,235 edges, and 34 connected components. The analysis suggests that similar genes responding to cold stress may also regulate development of Chinese cabbage. Using this network model, it is surmised that cold tolerance is strongly related to activation of chitinase antifreeze proteins by WRKY transcription factors and salicylic acid signaling, and to regulation of stomatal movement and starch metabolic processes for systemic acquired resistance in Chinese cabbage. Moreover, within 48 h, cold stress triggered transition from vegetative to reproductive phase and meristematic phase transition. In this study, we demonstrated that this network model could be used to precisely predict the functions of cold resistance genes in Chinese cabbage.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.4
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• pp.595-606
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• 2018

Objective: The Fusarium mycotoxins of deoxynivalenol (DON) and zerolenone (ZEN) cause health hazards for both humans and farm animals. Therefore, the main intention of this study was to reveal DON and ZEN effects on the mRNA expression of pro-inflammatory cytokines and other immune related genes in the liver of piglets. Methods: In the present study, 15 six-week-old piglets were randomly assigned to the following three different dietary treatments for 4 weeks: control diet, diet containing 8 mg DON/kg feed, and diet containing 0.8 mg ZEN/kg feed. After 4 weeks, liver samples were collected and sequenced using RNA-Seq to investigate the effects of the mycotoxins on genes and gene networks associated with the immune systems of the piglets. Results: Our analysis identified a total of 249 differentially expressed genes (DEGs), which included 99 upregulated and 150 downregulated genes in both the DON and ZEN dietary treatment groups. After biological pathway analysis, the DEGs were determined to be significantly enriched in gene ontology terms associated with many biological pathways, including immune response and cellular and metabolic processes. Consistent with inflammatory stimulation due to the mycotoxin-contaminated diet, the following Kyoto encyclopedia of genes and genomes pathways, which were related to disease and immune responses, were found to be enriched in the DEGs: allograft rejection pathway, cell adhesion molecules, graft-versus-host disease, autoimmune thyroid disease (AITD), type I diabetes mellitus, human T-cell leukemia lymphoma virus infection, and viral carcinogenesis. Genome-wide expression analysis revealed that DON and ZEN treatments downregulated the expression of the majority of the DEGs that were associated with inflammatory cytokines (interleukin 10 receptor, beta, chemokine [C-X-C motif] ligand 9), proliferation (insulin-like growth factor 1, major facilitator superfamily domain containing 2A, insulin-like growth factor binding protein 2, lipase G, and salt inducible kinase 1), and other immune response networks (paired immunoglobulin-like type 2 receptor beta, Src-like-adaptor-1 [SLA1], SLA3, SLA5, SLA7, claudin 4, nicotinamide N-methyltransferase, thyrotropin-releasing hormone degrading enzyme, ubiquitin D, histone $H_2B$ type 1, and serum amyloid A). Conclusion: In summary, our results demonstrated that high concentrations DON and ZEN disrupt immune-related processes in the liver.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.1
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• pp.138-148
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• 2018

Objective: Fusarium mycotoxins deoxynivalenol (DON) and zearalenone (ZEN), common contaminants in the feed of farm animals, cause immune function impairment and organ inflammation. Consequently, the main objective of this study was to elucidate DON and ZEN effects on the mRNA expression of pro-inflammatory cytokines and other immune related genes in the kidneys of piglets. Methods: Fifteen 6-week-old piglets were randomly assigned to three dietary treatments for 4 weeks: control diet, and diets contaminated with either 8 mg DON/kg feed or 0.8 mg ZEN/kg feed. Kidney samples were collected after treatment, and RNA-seq was used to investigate the effects on immune-related genes and gene networks. Results: A total of 186 differentially expressed genes (DEGs) were screened (120 upregulated and 66 downregulated). Gene ontology analysis revealed that the immune response, and cellular and metabolic processes were significantly controlled by these DEGs. The inflammatory stimulation might be an effect of the following enriched Kyoto encyclopedia of genes and genomes pathway analysis found related to immune and disease responses: cytokine-cytokine receptor interaction, chemokine signaling pathway, toll-like receptor signaling pathway, systemic lupus erythematosus (SLE), tuberculosis, Epstein-Barr virus infection, and chemical carcinogenesis. The effects of DON and ZEN on genome-wide expression were assessed, and it was found that the DEGs associated with inflammatory cytokines (interleukin 10 receptor, beta, chemokine [C-X-C motif] ligand 9, CXCL10, chemokine [C-C motif] ligand 4), proliferation (insulin like growth factor binding protein 4, IgG heavy chain, receptor-type tyrosine-protein phosphatase C, cytochrome P450 1A1, ATP-binding cassette sub-family 8), and other immune response networks (lysozyme, complement component 4 binding protein alpha, oligoadenylate synthetase 2, signaling lymphocytic activation molecule-9, ${\alpha}$-aminoadipic semialdehyde dehydrogenase, Ig lambda chain c region, pyruvate dehydrogenase kinase, isozyme 4, carboxylesterase 1), were suppressed by DON and ZEN. Conclusion: In summary, our results indicate that high concentrations of DON and ZEN suppress the inflammatory response in kidneys, leading to potential effects on immune homeostasis.

• Journal of Preventive Medicine and Public Health
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• v.47 no.6
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• pp.298-308
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• 2014

Objectives: To assess the current public participation in-local health policy and its implications through the analysis of policy networks in health center programs. Methods: We examined the decision-making process in sub-health center installations and the implementation process in metabolic syndrome management program cases in two districts ('gu's) of Seoul. Participants of the policy network were selected by the snowballing method and completed self-administered questionnaires. Actors, the interactions among actors, and the characteristics of the network were analyzed by Netminer. Results: The results showed that the public is not yet actively participating in the local public health policy processes of decision-making and implementation. In the decision-making process, most of the network actors were in the public sector, while the private sector was a minor actor and participated in only a limited number of issues after the major decisions were made. In the implementation process, the program was led by the health center, while other actors participated passively. Conclusions: Public participation in Korean public health policy is not yet well activated. Preliminary discussions with various stakeholders, including civil society, are needed before making important local public health policy decisions. In addition, efforts to include local institutions and residents in the implementation process with the public officials are necessary to improve the situation.

• Journal of Plant Biotechnology
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• v.37 no.2
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• pp.144-152
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• 2010

As the International Rice Genome Sequencing Project (IRGSP) was completed in 2005 and opened to the public, many countries are making a lot of investments in researches on the utilization of sequence information along with system development. Also, the necessity of the functional genomics researches using microarray is increased currently to secure unique genes related with major agricultural traits and analyze metabolic pathways. Microrarray enables efficient analysis of large scale gene expression and related transcription regulation. This review aims to introduce available microarrays made based on rice genome information and current status of gene expression analysis using these microarrays integrated with the databases available to the public. Also, we introduce the researches on the large scale functional analysis of genes related with useful traits and genetic networks. Understanding of the mechanism related with mutual interaction between proteins with co-expression among rice genes can be utilized in the researches for improving major agricultural traits. The direct and indirect interactions of various genes would provide new functionality of rice. The recent results of the various expression profiling analysis in rice will promote functional genomic researches in plants including rice and provide the scientists involved in applications researches with wide variety of expression informations.