• 식품보건융합연구
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• 제10권3호
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• pp.19-22
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• 2024

The field of synthetic biology has emerged in response to the ongoing progress in the life sciences. Advances have been made in medicine, farming, eating, making materials, and more. Synthetic biology is the exploration of using living organisms to create new organisms. By manipulating specific genes to express targeted proteins, proteins can be created that are both productive and cost-effective. Solid-phase extraction (SPE) and liquid-liquid extraction (LLE) are employed for protein separation during the production process involving microorganisms. This study centers on Scanning Probe Microscopy (SPM) to showcase its utility in the food industry and food management. SPE is predominantly utilized as a pretreatment method to eliminate impurities from samples. In comparison to LLE, this method presents benefits such as decreased time and labor requirements, streamlined solvent extraction, automation capabilities, and compatibility with various other analytical instruments. Anion exchange chromatography (AEC) utilizes a similar methodology. Pharmaceutical companies utilize these technologies to improve the purity of biopharmaceuticals, thereby guaranteeing their quality. Used in the food and beverage industry to test chemical properties of raw materials and finished products. This exemplifies the potential of these technologies to enhance industrial development and broaden the scope of applications in synthetic biology.

• Molecular & Cellular Toxicology
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• 제1권1호
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• pp.17-25
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• 2005

There are some critical drawbacks in the use of biomarkers for a global assessment of the toxicological impacts many chemicals and environmental pollutants have, primarily due to an individual biomarker's specificity for an explicit chemical or toxicant. In other words, the biomarker-based assessment methodology used to analyze toxicological effects lacks a high-throughput capability. Therefore, eco-toxicogenomics, or the study of toxicogenomics with organisms present within a given environmental locale, has recently been introduced with the advent of the so-called "-omics" era, which began with the creation of microarray technologies. Fish are comparable with humans in their toxicological responses and thus data from toxicogenomic studies performed with fish could be applied, with appropriate tools and implementation protocols, to the evaluation of environments where human or animal health is of concern. At present, there have been very active research streams for developing expression sequence tag (EST) databases (DBs) for zebra fish and rainbow trout. Even though few reports involve toxicogenomic studies with fish, a few groups have successfully fabricated and used cDNA microarrays or oligo DNA chips when studying the toxicological impacts of hypoxia or some toxicants with fish. Furthermore, it is strongly believed that this technology can also be implemented with non-model fish. With the standardization of DNA microarray technologies and ample progress in bioinformatics and proteomic technologies, data obtained from DNA microarray technologies offer not only multiple biomarker assays or an analysis of gene expression profiles, but also a means of elucidating gene networking, gene-gene relations, chemical-gene interactions, and chemical-chemical relationships. Accordingly, the ultimate target of eco-toxicogenomics should be to predict and map the pathways of stress propagation within an organism and to analyze stress networking.

• Asian-Australasian Journal of Animal Sciences
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• 제23권7호
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• pp.833-847
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• 2010

In the past decade, there have been many advances in whole-genome sequencing in domestic animals, as well as the development of "next-generation" sequencing technologies and high-throughput genotyping platforms. Consequently, these advances have led to the creation of the high-density SNP array as a state-of-the-art tool for genetics and genomics analyses of domestic animals. The emergence and utilization of SNP arrays will have significant impacts not only on the scale, speed, and expense of SNP genotyping, but also on theoretical and applied studies of quantitative genetics, population genetics and molecular evolution. The most promising applications in agriculture could be genome-wide association studies (GWAS) and genomic selection for the improvement of economically important traits. However, some challenges still face these applications, such as incorporating linkage disequilibrium (LD) information from HapMap projects, data storage, and especially appropriate statistical analyses on the high-dimensional, structured genomics data. More efforts are still needed to make better use of the high-density SNP arrays in both academic studies and industrial applications.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.366-370
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• 2005

Tissue microarry is one of the high throughput technologies in the post-genomic era. Using tissue microarray, the researchers are able to investigate large amount of gene expressions at the level of DNA, RNA, and protein The important aspect of tissue microarry is its ability to assess a lot of biomarkers which have been used in clinical practice. To manipulate the categorical data of tissue microarray, we applied Bayesian network classifier algorithm. We identified that Bayesian network classifier algorithm could analyze tissue microarray data and integrating prior knowledge about gastric cancer could achieve better performance result. The results showed that relevant integration of prior knowledge promote the prediction accuracy of survival status of the immunohistochemical tissue microarray data of 18 tumor suppressor genes. In conclusion, the application of Bayesian network classifier seemed appropriate for the analysis of the tissue microarray data with clinical information.

• Journal of Biosystems Engineering
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• 제41권2호
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• pp.116-125
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• 2016

Background: Microfluidics is of considerable importance in food and agricultural industries. Microfluidics processes low volumes of fluids in channels with extremely small dimensions of tens of micrometers. It enables the miniaturization of analytical devices and reductions in cost and turnaround times. This allows automation, high-throughput analysis, and processing in food and agricultural applications. Purpose: This review aims to provide information on the applications of microfluidics in the agro-food sector to overcome limitations posed by conventional technologies. Results: Microfluidics contributes to medical diagnosis, biological analysis, drug discovery, chemical synthesis, biotechnology, gene sequencing, and ecology. Recently, the applications of microfluidics in food and agricultural industries have increased. A few examples of these applications include food safety analysis, food processing, and animal production. This study examines the fundamentals of microfluidics including fabrication, control, applications, and future trends of microfluidics in the agro-food sector. Conclusions: Future research efforts should focus on developing a small portable platform with modules for fluid handling, sample preparation, and signal detection electronics.

• International Journal of Oral Biology
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• 제45권3호
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• pp.77-83
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• 2020

In the oral cavity, complex microbial community is shaped by various host and environmental factors. Extensive literature describing the oral microbiome in the context of oral health and disease is available. Advances in DNA sequencing technologies and data analysis have drastically improved the analysis of the oral microbiome. For microbiome study, bacterial 16S ribosomal RNA gene amplification and sequencing is often employed owing to the cost-effective and fast nature of the method. In this review, practical considerations for performing a microbiome study, including experimental design, molecular analysis technology, and general data analysis, will be discussed.

• 유전체소식지
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• 제5권4호
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• pp.9-16
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• 2005

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic expression data transforms the challenges m biomedical research into ones in bioinformatics. Clinical informatics has long developed technologies to imp개ve biomedical research by integrating experimental and clinical information systems. Biomedical informatics, powered by high throughput techniques, genomic-scale databases and advanced clinical information system, is likely to transform our biomedical understanding forever much the same way that biochemistry did to biology a generation ago. The emergence of healthcare and biomedical informatics revolutionizing both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics and prognostics.

• Asian Pacific Journal of Cancer Prevention
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• 제15권20호
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• pp.9045-9047
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• 2014

There have been overwhelming advances in molecular oncology and data obtained through high-throughput technologies have started to shed light on wide ranging molecular mechanisms that underpin cancer progression. Increasingly it is being realized that marine micro-organisms and the biodiversity of plankton are rich sources of various anticancer compounds. Marine derived compounds play major roles in inducing apoptosis in cancer cells. More importantly, various agents have been noted to enhance TRAIL induced apoptosis in cancer cells by functionalizing intrinsic and extrinsic pathways. In this commentary, a list of marine derived compounds reported to induce apoptosis is discussed.

• ALGAE
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• 제31권2호
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• pp.137-154
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• 2016

Next generation sequencing (NGS) technologies have revolutionized many areas of biological research due to the sharp reduction in costs that has led to the generation of massive amounts of sequence information. Analysis of large genome data sets is however still a challenging task because it often requires significant computer resources and knowledge of bioinformatics. Here, we provide a guide for an uninitiated who wish to analyze high-throughput NGS data. We focus specifically on the analysis of organelle genome and metagenome data and describe the current bioinformatic pipelines suited for this purpose.

• Journal of Genetic Medicine
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• 제12권1호
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• pp.6-11
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• 2015

Intellectual disability (ID) is the most common disability among people under the age of 20 years. In the absence of obvious non-genetic causes of ID, the majority of cases of severe ID are thought to have a genetic cause. The advent of technologies such as array comparative genomic hybridization, single nucleotide polymorphism genotyping arrays, and massively parallel sequencing has shown that de novo copy number variations and single nucleotide variations affecting coding regions are major causes of severe ID. This article reviews the genetic causes of ID along with diagnostic approaches for this disability.