• Molecular & Cellular Toxicology
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• v.3 no.sup4
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• pp.37.5-37.5
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• 2007

• BMB Reports
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• v.37 no.1
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• pp.53-58
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• 2004

With advances in determining the entire DNA sequence of the human genome, it is now critical to systematically identify the function of a number of genes in the human genome. These biological challenges, especially those in human diseases, should be addressed in human cells in which conventional (e.g. genetic) approaches have been extremely difficult to implement. To overcome this, several approaches have been initiated. This review will focus on the development of a novel 'chemical genetic/genomic approach' that uses small molecules to 'probe and identify' the function of genes in specific biological processes or pathways in human cells. Due to the close relationship of small molecules with drugs, these systematic and integrative studies will lead to the 'medicinal systems biology approach' which is critical to 'formulate and modulate' complex biological (disease) networks by small molecules (drugs) in human bio-systems.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.6
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• pp.376-384
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• 2016

Systems biology is an emerging field aiming at a systems level understanding of living organisms and focusing on the characteristics of the whole network of them. The emergence of systems biology is partly because of the availability of huge amounts of data on organisms and the extensive support of computational technologies as the tools for understanding complex biological systems. The scientific understanding of Korean medicine has been obstructed because of the lack of proper methods examining the complex nature and the unique property of it. However, systems biology could give a chance understanding Korean medicine objectively and scientifically. Pattern classification is a unique tool of Korean medicine to diagnose and treat patients and systems biology would give a useful tool to interpret pattern classification. Various omics technologies has been used to explain the relations between pattern classification and biological factors and then many characteristics of pattern classification in various diseases have been discovered. Therefore, pattern classification could be a bridge to understand the features and differences of western medicine and Korean medicine and it could be a basis to develop pattern-based personalized medicine.

• Molecules and Cells
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• v.41 no.6
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• pp.495-505
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• 2018

Several bacterial etiological agents of streptococcal disease have been associated with fish mortality and serious global economic loss. Bacterial identification based on biochemical, molecular, and phenotypic methods has been routinely used, along with assessment of morphological analyses. Among these, the molecular method of 16S rRNA sequencing is reliable, but presently, advanced genomics are preferred over other traditional identification methodologies. This review highlights the geographical variation in strains, their relatedness, as well as the complexity of diagnosis, pathogenesis, and various control methods of streptococcal infections. Several limitations, from diagnosis to control, have been reported, which make prevention and containment of streptococcal disease difficult. In this review, we discuss the challenges in diagnosis, pathogenesis, and control methods and suggest appropriate molecular (comparative genomics), cellular, and environmental solutions from among the best available possibilities.

• BMB Reports
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• v.44 no.1
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• pp.11-21
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• 2011

During the last decade small regulatory RNA (srRNA) emerged as central players in the regulation of gene expression in all kingdoms of life. Multiple pathways for srRNA biogenesis and diverse mechanisms of gene regulation may indicate that srRNA regulation evolved independently multiple times. However, small RNA pathways share numerous properties, including the ability of a single srRNA to regulate multiple targets. Some of the mechanisms of gene regulation by srRNAs have significant effect on the abundance of free srRNAs that are ready to interact with new targets. This results in indirect interactions among seemingly unrelated genes, as well as in a crosstalk between different srRNA pathways. Here we briefly review and compare the major srRNA pathways, and argue that the impact of srRNA is always at the system level. We demonstrate how a simple mathematical model can ease the discussion of governing principles. To demonstrate these points we review a few examples from bacteria and animals.

• Journal of Microbiology and Biotechnology
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• v.16 no.6
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• pp.832-848
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• 2006

Systems biology has recently become an important research paradigm that is anticipated to decipher the metabolic, regulatory, and signaling networks of complex living organisms on the whole organism level. Thus, various research outputs are being generated, along with the development of many tools and resources for systems biology research. Accordingly, this review provides a comprehensive summary of the current resources and tools for systems biology research that will hopefully be helpful to researchers involved in this field. The resources are categorized into the following five groups: genome information and analysis, transcriptome and proteome databases, metabolic profiling and metabolic control analysis, metabolic and regulatory information, and software for computational systems biology. A summary table and some future perspectives are also provided.

• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.529-535
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• 2007

Recently, an attempt to analyze and modify metabolic networks of living organisms in global level emerged with the benefit of development of high-throughput techniques, and it is generally called systems biology. Various systems biology studies have been carried out for the development of enhanced metabolite production systems. By modification of metabolic characteristics of microorganisms, metabolite productivities and yields obtained with metabolically engineered bacteria increased significantly compare with that obtained with wild type bacteria.

• Biodesign
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• v.5 no.3
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• pp.122-125
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• 2017

Receptor for advanced glycation end products (RAGE) is one of the single transmembrane domain containing receptors and causes various inflammatory diseases including diabetes and atherosclerosis. RAGE extracellular domain has three consecutive IgG-like domains (V-C₁-C₂ domain) which interact with various soluble ligands including heparan sulfate or HMGB1. Studies have shown that each ligand induces different oligomeric forms of RAGE which results in a ligand-specific signal transduction. The structure of mouse RAGE bound to heparan sulfate has been previously determined but the electron density map of heparan sulfate was too ambiguous that the exact position of heparin sulfate could not be defined. Furthermore, the complex structure of human RAGE and heparin sulfate still remains elusive. Therefore, to determine the structure, human RAGE was overexpressed using bacterial expression system and crystallized using the sitting drop method in the condition of 0.1 M sodium acetate trihydrate pH 4.6, 8 % (w/v) polyethylene glycol 4,000 at 290 K. The crystal diffracted to 3.6 Å resolution and the space group is C121 with unit cell parameters a= 206.04 Å, b= 68.64 Å, c= 98.73 Å, α= 90.00°, β= 90.62°, γ= 90.00°.

• Bulletin of Food Technology
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• v.24 no.2
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• pp.187-195
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• 2011

• BMB Reports
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• v.41 no.3
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• pp.184-193
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• 2008

Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples.