• BMB Reports
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• v.45 no.7
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• pp.377-389
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• 2012

Food fermentations have enhanced human health since the dawn of time and remain a prevalent means of food processing and preservation. Due to their cultural and nutritional importance, many of these foods have been studied in detail using molecular tools, leading to enhancements in quality and safety. Furthermore, recent advances in high-throughput sequencing technology are revolutionizing the study of food microbial ecology, deepening insight into complex fermentation systems. This review provides insight into novel applications of select molecular techniques, particularly next-generation sequencing technology, for analysis of microbial communities in fermented foods. We present a guideline for integrated molecular analysis of food microbial ecology and a starting point for implementing next-generation analysis of food systems.

• Genomics & Informatics
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• v.16 no.4
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• pp.29.1-29.5
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• 2018

Hybrid capture-based targeted sequencing is being used increasingly for genomic variant profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing polymerase chain reaction biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various study groups for their own purposes. Due to this provincial usage of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared and pooled together, and an 8-plexed capture library was processed to the enrichment step before 150-bp paired-end sequencing with Illumina HiSeq series. For the analysis, we evaluated several published tools. We focused mainly on the compatibility of the input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of the quality and efficiency of conducted experiments.

• Molecules and Cells
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• v.45 no.9
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• pp.610-619
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• 2022

Cellular senescence plays a paradoxical role in tumorigenesis through the expression of diverse senescence-associated (SA) secretory phenotypes (SASPs). The heterogeneity of SA gene expression in cancer cells not only promotes cancer stemness but also protects these cells from chemotherapy. Despite the potential correlation between cancer and SA biomarkers, many transcriptional changes across distinct cell populations remain largely unknown. During the past decade, single-cell RNA sequencing (scRNA-seq) technologies have emerged as powerful experimental and analytical tools to dissect such diverse senescence-derived transcriptional changes. Here, we review the recent sequencing efforts that successfully characterized scRNA-seq data obtained from diverse cancer cells and elucidated the role of senescent cells in tumor malignancy. We further highlight the functional implications of SA genes expressed specifically in cancer and stromal cell populations in the tumor microenvironment. Translational research leveraging scRNA-seq profiling of SA genes will facilitate the identification of novel expression patterns underlying cancer susceptibility, providing new therapeutic opportunities in the era of precision medicine.

• Interdisciplinary Bio Central
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• v.4 no.3
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• pp.6.1-6.12
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• 2012

Parkinson's disease (PD) is a complicated neurodegenerative disorder although it is oftentimes defined by clinical motor symptoms originated from age dependent and progressive loss of dopaminergic neurons in the midbrain. The pathogenesis of PD involves dopaminergic and nondopaminergic neurons in many brain regions and the molecular mechanisms underlying the death of different cell types still remain to be elucidated. There are indications that PD causing disease processes occur in a global scale ranging from DNA to RNA, and proteins. Several PD-associated genes have been reported to play diverse roles in controlling cellular functions in different levels, such as chromatin structure, transcription, processing of mRNA, translational modulation, and posttranslational modification of proteins. The advent of quantitative high throughput screening (HTS) tools makes it possible to monitor systemic changes in DNA, RNA and proteins in PD models. Combined with dopamine neuron isolation or derivation of dopamine neurons from PD patient specific induced pluripotent stem cells (PD iPSCs), HTS techonologies will provide opportunities to draw PD causing sequences of molecular events in pathologically relevant PD samples. Here I discuss previous studies that identified molecular functions in which PD genes are involved, especially those signaling pathways that can be efficiently studied using HTS methodologies. Brief descriptions of quantitative and systemic tools looking at DNA, RNA and proteins will be followed. Finally, I will emphasize the use and potential benefits of PD iPSCs-derived dopaminergic neurons to screen signaling pathways that are initiated by PD linked gene mutations and thus causative for dopaminergic neurodegneration in PD.

• Proceedings of the Korean Vacuum Society Conference
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• 1998.02a
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• pp.20-20
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• 1998

I Ion beam technology has recently attracted much interest because it has exciting t technological p아:ential for surface analysis, ion beam mixing, surface cleaning and etching i in thin film growth and semiconductor fabrication processes, etc. Es야~cially, ion beam s sputtering has been widely used for sputter depth profiling with x-photoelectron S spectroscopy (XPS) , Auger electron s$\pi$~troscopy(AES), and secondary-ion mass S야i따oscopy(SIMS). However, The problem of surface compositional ch없1ge due to ion b bombardment remains to be understo여 없ld solved. So far sputtering processes have been s studied by s따face an외ysis tools such as XPS, AES, and SIMS which use the sputtering p process again. It would be improbable to measure the modified surface composition profiles a accurately due to ion beam bombardment with surface analysis techniques based on sputter d depth profiling. However, recently Medium energy ion scattering spectroscopy(MEIS) has b been applied to study the sputtering of solid surface at ion bombardment and has been p proved that it has been extremely valuable in probing the surface composition 뻐d s structure nondestructively and quantita디vely with less than 1.0 nm depth resolution. To u understand the sputtering processes of solid surface at ion bombardment, The Molecular D Dynamics(MD) and Monte Carlo(MC) simulation has been used and give an intimate i insight into the sputtering processes of solid surfaces. In this presentation, the sputtering processes of alloys and compound samples at ion b bombardment will be reviewed and the MEIS results for the Ar+ sputter induced altered l layer of the TazOs thin film 뻐dd없nage profiling of Ar+ ion sputt얹"ed Si(100) surface will b be discussed with the results of MD and MC simulation.tion.

• Food Science and Industry
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• v.50 no.1
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• pp.2-10
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• 2017

Human have eaten various traditional fermented foods for a numbers of million years for health benefit as well as survival. The beneficial effects of fermented foods have been resulted from complex microbial communications within the fermented foods. Therefore, the holistic approaches for individual identification and complete microbial profiling involved in their communications have been of interest to food microbiology fields. Microbiome is the ecological community of microorganisms that literally share our environments including foods as well as human body. However, due to the limitation of culture-dependent methods such as simple isolations of just culturable microorganisms, the culture-independent methods have been consistently developed, resulting in new light on the diverse non-culturable and hitherto unknown microorganisms, and even microbial communities in the fermented foods. For the culture-independent approaches, the food microbiome has been deciphered by employing various molecular analysis tools such as fluorescence in situ hybridization, quantitative PCR, and denaturing gradient gel-electrophoresis. More recently, next-generation-sequencing (NGS) platform-based microbiome analysis has been of interest, because NGS is a powerful analytical tool capable of resolving the microbiome in respect to community structures, dynamics, and activities. In this overview, the development status of analysis tools for the fermented food microbiome is covered and research trend for NGS-based food microbiome analysis is also discussed.

• BMB Reports
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• v.45 no.8
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• pp.442-451
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• 2012

Milk is an important fluid in glycobiology because it contains a number of short carbohydrate chains either free or as glycoconjugates. These compounds as a class are the most abundant component and benefit the infant by developing and maintaining the infant's gut flora. New and emerging methods for oligosaccharide analysis have been developed to study milk. These methods allow for the rapid profiling of oligosaccharide mixtures with quantitation. With these tools, the role of oligosaccharide in milk is being understood. They further point to how oligosaccharide analysis can be performed, which until now has been very difficult and have lagged significantly those of other biopolymers.

• International Journal of Industrial Entomology and Biomaterials
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• v.15 no.2
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• pp.115-122
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• 2007

As the genome of B.mori is available in GenBank and the EST database of B.mori is expanding, identification of novel genes of B.mori is conceivable by data-mining techniques. We used the in silico cloning method to get the vacuolar-type $H^+-ATP$ synthetase (V-ATPase) c subunit (16 kDa proteolipid subunit) gene of B.mori and analysed with bioinformatics tools. The result was confirmed by RT-PCR and sequencing. The V-ATPase c subunit cDNA contains a 468 bp ORF. The ORF encoded a 155-residue protein that showed extensive homology with V-ATPase c subunits from other 15 species and contained four membrane-spanning helices. Tissue expression pattern analysis revealed that V-ATPase c expressed strongly in Malpighian tubules, not in fat body. This gene has been registered in GenBank under the accession number EU082222.

• Journal of the Korean Chemical Society
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• v.63 no.2
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• pp.78-84
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• 2019

High-resolution $^1H$ NMR spectroscopic technique has been widely used as one of the most powerful analytical tools in food chemistry as well as to define molecular structure. The $^1H$ NMR spectra-based metabolomics has focused on classification and chemometric analysis of complex mixtures. The principal component analysis (PCA), an unsupervised clustering method and used to reduce the dimensionality of multivariate data, facilitates direct peak quantitation and pattern recognition. Using a combination of these techniques, the various green teas and black teas brewed were investigated via metabolite profiling. These teas were characterized based on the leaf size and country of cultivation, respectively.

• Molecules and Cells
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• v.46 no.2
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• pp.99-105
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• 2023

Tumors are surrounded by a variety of tumor microenvironmental cells. Profiling individual cells within the tumor tissues is crucial to characterize the tumor microenvironment and its therapeutic implications. Since single-cell technologies are still not cost-effective, scientists have developed many statistical deconvolution methods to delineate cellular characteristics from bulk transcriptome data. Here, we present an overview of 20 deconvolution techniques, including cutting-edge techniques recently established. We categorized deconvolution techniques by three primary criteria: characteristics of methodology, use of prior knowledge of cell types and outcome of the methods. We highlighted the advantage of the recent deconvolution tools that are based on probabilistic models. Moreover, we illustrated two scenarios of the common application of deconvolution methods to study tumor microenvironments. This comprehensive review will serve as a guideline for the researchers to select the appropriate method for their application of deconvolution.