• Journal of Life Science
• /
• v.29 no.2
• /
• pp.181-190
• /
• 2019

The purpose of this study was to acquire the active compounds of Anisi stellati fructus (ASF) and to analyze the genes and diseases it targets, focusing on its antibacterial effects using a system pharmacological analysis approach. Active compounds of ASF were obtained through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. This contains the pharmacokinetic properties of active compounds and related drug-target-disease networks, which is a breakthrough in silico approach possible at the network level. Gene information of targets was gathered from the UnitProt Database, and gene ontology analysis was performed using the David 6.8 Gene Functional Classification Tool. A total of 201 target genes were collected, which corresponded to the nine screened active compounds, and 47 genes were found to act on biological processes related to antimicrobial activity. The representative active compounds involved in antibacterial action were luteolin, kaempferol, and quercetin. Among their targets, Chemokine ligand2, Interleukin-10, Interleukin-6, and Tumor Necrosis Factor were associated with more than three antimicrobial biological processes. This study has provided accurate evidence while saving time and effort to select future laboratory research materials. The data obtained has provided important data for infection prevention and treatment strategies.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.265-271
• /
• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• Journal of Plant Biotechnology
• /
• v.44 no.3
• /
• pp.264-270
• /
• 2017

Brassinosteroid (BR), a plant steroid hormone, plays a critical role in the growth and developmental processes through its canonical signaling and crosstalk with various internal and external signaling pathways. Recent studies have revealed the essential interplay mechanisms between BR and ABA during seed germination and early seedling establishment. However, molecular mechanisms for this important signaling crosstalk are largely unknown. To understand the crosstalk between BR-mediated signaling pathways and ABA functions during early seedling development, we carried out a comparative genome-wide transcriptome analysis with an Agilent Arabidopsis $4{\times}44K$ oligo chip. We selected and compared the expression patterns of ABA response genes in ABA-insensitive bes1-D mutant with wild type seedlings on which ABA was exogenously applied. As a result, we identified 2,353 significant differentially expressed genes (DEGs) in ABA-treated bes1-D and wild type seedlings. GO enrichment analysis revealed that ABA signaling, response, and metabolism were critically down-regulated by BR-activated signaling pathways. In addition, the genome-wide transcriptome analysis data revealed that BR-regulated signaling pathways were tightly connected to diverse signal cues including abiotic/biotic stress, auxin, ROS etc. In this study, we newly identified the molecular mechanisms of BR-mediated repression of ABA signaling outputs. Also, our data suggest that interplay among diverse signaling pathways is critical for the adaptive response of the plant to various environmental factors.

• Korean Journal of Environmental Biology
• /
• v.39 no.2
• /
• pp.195-206
• /
• 2021

In 2020, South Korea initiated research and development of a longitudinal connectivity evaluation between upstream and downstream based on stream ecosystem health. This study analyzed the migration of upstream and downstream migratory fish species, fish distribution characteristics, trophic guilds, tolerance guilds, and species composition changes from 2015 to 2020 at Songrim weir in Yeongok stream, where the cross-structure of an ice harbor-type fishway for fish movement was recently improved. A total of 5,136 fish, including 36 species, were collected and three major migratory fishes were identified, namely, Tribolodon hakonensis, Plecoglossus altivelis altivelis, and Oncorhynchus keta. According to the comparative analysis before (Pre-I) and after (Post-I) improvement of the fishway, the relative abundance of primary freshwater fish increased in the upstream section, while the number of migratory fishes decreased. The fish species that used the fishway in the Songrim weir were Tribolodon hakonensis (58.4%) and Plecoglossus altivelis altivelis(11.8%). According to the Wilcoxon Signed-Rank Test migratory fish showed a statistically significant difference (p<0.05) in the upstream and downstream, showing a biological improvement effect of the crossstructure. On the other hand, the annual change of migratory fish based on the MannKendall trend test did not significantly increase or decrease (p>0.05). Therefore, in the fish passage improvement project, it is necessary not only for physical, hydrological, and structural tests, but also for pre- and post-biological tests on the use and improvement effect of fishway.

• Electronics and Telecommunications Trends
• /
• v.36 no.3
• /
• pp.106-118
• /
• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.77-80
• /
• 2007

현재 생명공학은 급속도로 발전하고 있으며, 이를 통해 만들어지는 생물정보의 양은 기하급수적으로 늘어나고 있다. 이러한 것을 가능하게 하는 기술 중의 하나인 마이크로어레이 기법은 현재 질병의 진단 및 신약 개발 등을 위해 사용되고 있다. 마이크로어레이 유전자 발현에 관한 분석은 크게 유의한 유전자 추출, 클러스터링, 분류 및 유전자 네트워크 구축 등으로 볼 수 있다. 유의한 유전자 식별을 위한 통계학적 방법으로 T-test 및 Wilcoxon Rank Sum test 등이 있다. 최근에는 수정인자를 추가하거나 혹은 퍼지이론 등의 지능정보 이론을 추가하여 그 계산결과를 좀 더 상세화하고 세분화하는 연구들이 계속되고 있다. 본 논문에서는 두 개의 그룹에서 발현된 유전자들 중 유의하게 발현되는 유전자를 식별하기 위한 방법으로 퍼지이론을 도입하여 유의한 유전자를 규명하는 FST(Fuzzy Significance Test) 방법을 제안한다.

• The Journal of the Korea Contents Association
• /
• v.14 no.11
• /
• pp.467-475
• /
• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• Journal of Life Science
• /
• v.23 no.11
• /
• pp.1409-1414
• /
• 2013

Lymph node (LN) is the sites where mature lymphocytes become stimulated to respond to invading pathogens in the body. Lymphocytes screen the surfaces of pathogen-carrying antigen-presenting cells for cognate antigens, while moving along stromal structural back bone. Fibroblastic reticular cells (FRC) is stromal cell forming the 3 dimensional structure networks of the T cell rich zones in LN, and provide a guidance path for immigrating T lymphocytes. In these cooperative environments, the cell to cell bidirectional interactions between FRC and T cells in LN are therefore essential to the normal functioning of these tissues. Not only do FRCs physically construct LN architecture but they are essential for regulating T cell biology within these domains. FRC interact closely with T lymphocytes, is providing scaffolds, secreting soluble factors including cytokine in which FRCs influence T cell immune response. More recently, FRC have been found to induce peripheral T cell tolerance and regulate the extent to which newly activated T cells proliferate within LN. Thus, FRC-T cell crosstalk has important consequences for regulating immune cell function within LN. In addition, FRC have profound effects on innate immune response by secreting anti-microbial peptides and complement, etc in the inflammatory milieu. In summary, we propose a model in which FRC engage in a bidirectional touch to increase the T cell biological efficiency between FRC and T cells. This collaborative feedback loop may help to maintain tissue function during inflammation response.

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

• The KIPS Transactions:PartB
• /
• v.18B no.2
• /
• pp.67-72
• /
• 2011

Single nucleotide polymorphisms (SNPs) are a very important tool for the study of human genome structure. Cluster analysis of the large amount of gene expression data is useful for identifying biologically relevant groups of genes and for generating networks of gene-gene interactions. In this paper we compared the clusters of SNPs within asthma group and normal control group obtained by using hierarchical cluster analysis method with entropy distance. It appears that the 5-cluster collections of the two groups are significantly different. We searched the best set of SNPs that are useful for diagnosing the two types of asthma using representative SNPs of the clusters of the asthma group. Here support vector machines are used to evaluate the prediction accuracy of the selected combinations. The best combination model turns out to be the five-locus SNPs including one on the gene ALOX12 and their accuracy in predicting aspirin tolerant asthma disease risk among asthmatic patients is 66.41%.