• Journal of the Economic Geographical Society of Korea
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• v.6 no.2
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• pp.293-306
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• 2003

This paper aims to clarify the change in industrial structure and industry itself, and makes suggestions for the industrial development direction at transitional periods in the Chungcheongbuk-do(province) region. Because profits of regional gross production in Chungcheongbuk-do region flow out of the region, basic industries must be brought up. For this phenomenon, main manufacturing must be developed for the industrial power of the next generation of high added values that combined with digital industry; the petrochemistry, semiconductor industry as major type of industry, and automobile industry as minor type of industry. Also for supporting industry, education service, health and welfare, research and development services that are knowledge-based service industries in Chungcheongbuk-do region, must be formated the network among corporations and constructed regional innovation system linked with educational institutions, precision chemistry industry and biology technology as major type of industry, and precision machinery and tools industry as minor type of industry.

• Genomics & Informatics
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• v.4 no.3
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• pp.125-128
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• 2006

We present an openfree hypertext (also known as wiki) web cluster called BioCC. BioCC is a novel wiki farm that lets researchers create hundreds of biological web sites. The web sites form an organic information network. The contents of all the sites on the BioCC wiki farm are modifiable by anonymous as well as registered users. This enables biologists with diverse backgrounds to form their own Internet bio-communities. Each community can have custom-made layouts for information, discussion, and knowledge exchange. BioCC aims to form an ever-expanding network of openfree biological knowledge databases used and maintained by biological experts, students, and general users. The philosophy behind BioCC is that the formation of biological knowledge is best achieved by open-minded individuals freely exchanging information. In the near future, the amount of genomic information will have flooded society. BioGG can be an effective and quickly updated knowledge database system. BioCC uses an opensource wiki system called Mediawiki. However, for easier editing, a modified version of Mediawiki, called Biowiki, has been applied. Unlike Mediawiki, Biowiki uses a WYSIWYG (What You See Is What You Get) text editor. BioCC is under a share-alike license called BioLicense (http://biolicense.org). The BioCC top level site is found at http://bio.cc/

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.281-287
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• 2021

Bioinformatics is formed with a blend of biology and informatics technologies and it employs the statistical methods and approaches for attending the concerning issues in the domains of nutrition, medical research and towards reviewing the living environment. The ceaseless growth of DNA sequencing technologies has resulted in the production of voluminous genomic data especially the DNA sequences thus calling out for increased storage and bandwidth. As of now, the bioinformatics confronts the major hurdle of management, interpretation and accurately preserving of this hefty information. Compression tends to be a beacon of hope towards resolving the aforementioned issues. Keeping the storage efficiently, a methodology has been recommended which for attending the same. In addition, there is introduction of a competent algorithm that aids in exact matching of small pattern. The DNA representation sequence is then implemented subsequently for determining 2 bases to 6 bases matching with the remaining input sequence. This process involves transforming of DNA sequence into an ASCII symbols in the first level and compress by using LZ77 compression method in the second level and after that form the grid variables with size 3 to hold the 100 characters. In the third level of compression, the compressed output is in the grid variables. Hence, the proposed algorithm S_Pattern DNA gives an average better compression ratio of 93% when compared to the existing compression algorithms for the datasets from the UCI repository.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.196-202
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• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.

• Journal of Korean Society on Water Environment
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• v.33 no.5
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• pp.511-524
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• 2017

This study was carried out for the purpose of creating a restoration plan to improve the ecological quality of the Changwon and Nam streams. Based upon the results of comprehensive diagnostic assessment, restoration priority was given to the upstream reach, where conservation status is relatively superior. Restoration level was usually determined to practice active restoration as conservation, and the states of both Changwon and Nam streams were not so good. Restoration plans, by reach, were classified into "upstream", "midstream", and "downstream" were suggested in both terms of horizontal section frame and vegetation-based on the result of diagnostic assessment and the reference information. "Upstream", "mid-stream" and the "downstream" of Changwon and Nam streams were classified into "small-gravel- mountainous", "small-sand-plain", and "small-clay-plain streams" respectively (based on scale, and substrate and slope of river bed). The spatial arrangement of vegetation was laid out in diagram form by reflecting micro-topography and the water level of the horizontal section of river. Information regarding species composition was recommended as dominant species, which appear frequently in three vegetation zones composed of herbaceous plants, shrubs and trees and sub-tree- dominated zones divided by reflecting disturbance regime, depending on position on the horizontal section of river. Moreover, there have been prepared not only plans to improve the terrestrial ecosystems around the streams but also plans to create ecological networks, which can serve to improve the ecologic quality of the whole regional environment by serving to connect streams and terrestrial ecosystems, a process probably necessary and definitely recommended to realize true (genuine) restoration. Plans for ecological parks and networks were prepared by mimicking the species composition of Alnus japanica community, Zelkova serrata community, Carpinus laxiflora community, Quercus aliena community, and Q. serrata community.

• Journal of Microbiology and Biotechnology
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• v.34 no.8
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• pp.1617-1626
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• 2024

Various antibiotic-resistant bacteria (ARB) are known to induce repeated pulmonary infections and increase morbidity and mortality. A thorough knowledge of antibiotic resistance is imperative for clinical practice to treat resistant pulmonary infections. In this study, we used a reads-based method and an assembly-based method according to the metagenomic next-generation sequencing (mNGS) data to reveal the spectra of ARB and corresponding antibiotic resistance genes (ARGs) in samples from patients with pulmonary infections. A total of 151 clinical samples from 144 patients with pulmonary infections were collected for retrospective analysis. The ARB and ARGs detection performance was compared by the reads-based method and assembly-based method with the culture method and antibiotic susceptibility testing (AST), respectively. In addition, ARGs and the attribution relationship of common ARB were analyzed by the two methods. The comparison results showed that the assembly-based method could assist in determining pathogens detected by the reads-based method as true ARB and improve the predictive capabilities (46% > 13%). ARG-ARB network analysis revealed that assembly-based method could promote determining clear ARG-bacteria attribution and 101 ARGs were detected both in two methods. 25 ARB were obtained by both methods, of which the most predominant ARB and its ARGs in the samples of pulmonary infections were Acinetobacter baumannii (ade), Pseudomonas aeruginosa (mex), Klebsiella pneumoniae (emr), and Stenotrophomonas maltophilia (sme). Collectively, our findings demonstrated that the assembly-based method could be a supplement to the reads-based method and uncovered pulmonary infection-associated ARB and ARGs as potential antibiotic treatment targets.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.616-625
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• 2015

Currently, oriental medicine research is focused with modern research technology and validate it's various biochemical effect by combining with molecular biology technology. But there are few searching system for finding biochemical mechanism which is related to major compounds in oriental medicine. In this research, we aimed developing korean herb database based on text-mining system by analyzing PubMed data. We have developed prototype system for searching chemical, gene and biological relation in oriental medicine. It is characterized by modern oriental medicine research trend with major chemical, gene and protein information. Analysis results can be searched on the prototype system with visualization of the biological interactions.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.1
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.

• BMB Reports
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• v.35 no.2
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• pp.213-219
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• 2002

Malonyl-CoA decarboxylase (E.C.4.1.1.9) catalyzes the conversion of malonyl-CoA to acetyl-CoA. Although the metabolic role of this enzyme has not been fully defined, it has been reported that its deficiency is associated with mild mental retardation, seizures, hypotonia, cadiomyopathy, developmental delay, vomiting, hypoglycemia, metabolic acidosis, and malonic aciduria. Here, we isolated a cDNA clone for malonyl CoA decarboxylase from a rat brain cDNA library, expressed it in E. coli, and characterized its biochemical properties. The full-length cDNA contained a single open-reading frame that encoded 491 amino acid residues with a calculated molecular weight of 54, 762 Da. Its deduced amino acid sequence revealed a 65.6% identity to that from the goose uropigial gland. The sequence of the first 38 amino acids represents a putative mitochondrial targeting sequence, and the last 3 amino acid sequences (SKL) represent peroxisomal targeting ones. The expression of malonyl CoA decarboxylase was observed over a wide range of tissues as a single transcript of 2.0 kb in size. The recombinant protein that was expressed in E. coli was used to characterize the biochemical properties, which showed a typical Michaelis-Menten substrate saturation pattern. The $K_m$ and $V_{max}$ were calculated to be $68\;{\mu}M$ and $42.6\;{\mu}mol/min/mg$, respectively.