• Molecules and Cells
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• v.39 no.9
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• pp.692-698
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• 2016

Advances in next generation sequencing (NGS) technologies have enabled population-level studies for many animals to unravel the relationships between genotypic differences and traits of specific populations. The objective of this study was to perform evolutionary analysis of single nucleotide polymorphisms (SNP) in genes of Korean native cattle Hanwoo in comparison to SNP data from four other cattle breeds (Jersey, Simmental, Angus, and Holstein) and four related species (pig, horse, human, and mouse) obtained from public databases through NGS-based resequencing. We analyzed population structures and differentiation levels for the five cattle breeds and estimated species-specific SNPs with their origins and phylogenetic relationships among species. In addition, we identified Hanwoo-specific genes and proteins, and determined distinct changes in protein-protein interactions among five species (cattle, pig, horse, human, mouse) in the STRING network database by additionally considering indirect protein interactions. We found that the Hanwoo population was clearly different from the other four cattle populations. There were Hanwoo-specific genes related to its meat trait. Protein interaction rewiring analysis also confirmed that there were Hanwoo-specific protein-protein interactions that might have contributed to its unique meat quality.

• Korea Information Processing Society Review
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• v.15 no.2
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• pp.15-28
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• 2008

The Korea UK e-Science Collaboration project has been aimed at supporting research and collaboration between Korean and UK researchers. Its goal is to benefit the nation by reducing cost and time in constructing the National e-Science Research Environment' by studying and benchmarking the cases in countries that have already procured advanced technologies in the area. Two joint workshops were held in a year where researchers from the two countries had the opportunities to share their research results with each other. Also, the project has supported exchanges of researchers fostering expertise in the field. In the course of the project, the e-Science Centre in the UK and KISTI have signed MoU(Memorandum of Understanding) in 2006. Moreover, there have been active research collaboration between Korea and the UK. The University of Southampton will share the BioSimGrid data with the Korean counterpart, and the University of York has provided the AURA software. In the future, KISTI and the UK NGS(National Grid Service) will organize a working group at OGF that will work mainly on the standardization of Parameter Sweep and bring it to lead the global standard. KISTI will include its own AURORA system into OMI-UK software stack, which will enable access to NGS resources through AURORA user application. The collaboration with the UK has opened up more opportunities for collaboration with other countries as well. KISTI and HLRS in Germany have agreed to share the COVISE and will have research exchanges. As such, it is expected that Korea will play a major role in e-Science research by building strategic and systematic collaborative relations with its International partners.

• BMB Reports
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• v.49 no.12
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• pp.662-670
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• 2016

The human oral cavity contains a highly personalized microbiome essential to maintaining health, but capable of causing oral and systemic diseases. Thus, an in-depth definition of "healthy oral microbiome" is critical to understanding variations in disease states from preclinical conditions, and disease onset through progressive states of disease. With rapid advances in DNA sequencing and analytical technologies, population-based studies have documented the range and diversity of both taxonomic compositions and functional potentials observed in the oral microbiome in healthy individuals. Besides factors specific to the host, such as age and race/ethnicity, environmental factors also appear to contribute to the variability of the healthy oral microbiome. Here, we review bioinformatic techniques for metagenomic datasets, including their strengths and limitations. In addition, we summarize the interpersonal and intrapersonal diversity of the oral microbiome, taking into consideration the recent large-scale and longitudinal studies, including the Human Microbiome Project.

• Korean Journal of Agricultural Science
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• v.44 no.3
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• pp.318-324
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• 2017

With the development of next-generation sequencing (NGS), a cutting-edge technology, genotype-by-sequencing (GBS) became available at a low cost per sample. GBS makes it possible to customize the process of library preparation to obtain high-quality single nucleotide polymorphisms (SNPs) in the most efficient way. However, a GBS library is hard to construct due to fine-tuning of concentration of each reagent and set-up. The major reason for this is the presence of undigested genomic DNA (gDNA) owing to the efficiency of different restriction enzymes for different species with unknown reasons. Therefore, this proof-concept study is to demonstrate the unpredictable patterns of enzyme digestion from various plants in order to make the reader aware of the caution needed when choosing restriction enzymes for their GBS library preparations. Indeed, no pattern was found for the digestibility of gDNA samples and restriction enzymes in the current study. We suggest that more data should be accumulated on this matter to help researchers who want to apply GBS technologies in a variety of genetic approaches.

• Korean Journal of Head & Neck Oncology
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• v.39 no.1
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• pp.1-9
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• 2023

Technological advancement in human genome analysis and ICT (information & communication technologies) brought 'precision medicine' into our clinical practice. Precision medicine is a novel medical approach that provides personalized treatments tailored to each individual by precisely segmenting patient populations, based on robust data including a person's genetic information, disease information, lifestyle information, etc. Precision medicine has a potential to be applied to treating a range of tumors, in addition to non-small cell lung cancer, in which precision oncology has been actively practiced. In this article, we are reviewing precision medicine in head and neck cancer (HNC) with focus on tumor agnostic biomarkers and treatments such as NTRK, MSI-H/dMMR, TMB-H and BRAF V600E, all of which were recently approved by U.S. Food and Drug Administration (FDA).

• Genomics & Informatics
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• v.21 no.2
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• pp.24.1-24.7
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• 2023

Assays of clinical diagnosis and species identification using molecular markers are performed according to a quantitative method in consideration of sensitivity, cost, speed, convenience, and specificity. However, typical polymerase chain reaction (PCR) assay is difficult to quantify and have various limitations. In addition, to perform quantitative analysis with the quantitative real-time PCR (qRT-PCR) equipment, a standard curve or normalization using reference genes is essential. Within the last a decade, previous studies have reported that the digital PCR (dPCR) assay, a third-generation PCR, can be applied in various fields by overcoming the shortcomings of typical PCR and qRT-PCR assays. We selected Stilla Naica System (Stilla Technologies), Droplet Digital PCR Technology (Bio-Rad), and Lab on an Array Digital Real-Time PCR analyzer system (OPTOLANE) for comparative analysis among the various droplet digital PCR platforms currently in use commercially. Our previous study discovered a molecular marker that can distinguish Hanwoo species (Korean native cattle) using Hanwoo-specific genomic structural variation. Here, we report the pros and cons of the operation of each dPCR platform from various perspectives using this species identification marker. In conclusion, we hope that this study will help researchers to select suitable dPCR platforms according to their purpose and resources.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.29-43
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• 2014

The development of NGS technologies, such as scientific workflows, has reduced the time required for decoding DNA sequences. Although the automated technologies change the genome sequence analysis environment, limited computing resources still pose problems for the analysis. Most scientific workflow systems are pre-built platforms and are highly complex because a lot of the functions are implemented into one system platform. It is also difficult to apply components of pre-built systems to a new system in the cloud environment. Cloud computing technologies can be applied to the systems to reduce analysis time and enable simultaneous analysis of massive DNA sequence data. Web service techniques are also introduced for improving the interoperability between DNA sequence analysis systems. The workflow-based middleware, which supports Web services, DBMS, and cloud computing, is proposed in this paper for expecting to reduceanalysis time and aiding lightweight virtual instances. It uses DBMS for managing the pipeline status and supporting the creation of lightweight virtual instances in the cloud environment. Also, the RESTful Web services with simple URI and XML contents are applied for improving the interoperability. The performance test of the system needs to be conducted by comparing results other developed DNA analysis services at the stabilization stage.

• Genomics & Informatics
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• v.10 no.1
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• pp.33-39
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• 2012

High-throughput genomic technologies (HGTs), including next-generation DNA sequencing (NGS), microarray, and serial analysis of gene expression (SAGE), have become effective experimental tools for cancer genomics to identify cancer-associated somatic genomic alterations and genes. The main hurdle in cancer genomics is to identify the real causative mutations or genes out of many candidates from an HGT-based cancer genomic analysis. One useful approach is to refer to known cancer genes and associated information. The list of known cancer genes can be used to determine candidates of cancer driver mutations, while cancer gene-related information, including gene expression, protein-protein interaction, and pathways, can be useful for scoring novel candidates. Some cancer gene or mutation databases exist for this purpose, but few specialized tools exist for an automated analysis of a long gene list from an HGT-based cancer genomic analysis. This report presents a new web-accessible bioinformatic tool, called CaGe, a cancer genome annotation system for the assessment of candidates of cancer genes from HGT-based cancer genomics. The tool provides users with information on cancer-related genes, mutations, pathways, and associated annotations through annotation and browsing functions. With this tool, researchers can classify their candidate genes from cancer genome studies into either previously reported or novel categories of cancer genes and gain insight into underlying carcinogenic mechanisms through a pathway analysis. We show the usefulness of CaGe by assessing its performance in annotating somatic mutations from a published small cell lung cancer study.

• Journal of KIISE
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• v.42 no.12
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• pp.1584-1589
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• 2015

With the advancement of next-generation sequencing (NGS) technologies, various genome browsers have been introduced. Because existing browsers focus on comparison of the genomic data of extant species, however, there is a need for a genome browser for ancestral genomes and their evolution. In this paper, we introduce a genome browser, AGB (Ancestral Genome Browser), that displays ancestral genome data reconstructed from existing species. With AGB, it is possible to trace genomic variations that occurred during evolution in a simple and intuitive way. We explain the capability of AGB in terms of visualizing ancestral genomic information and evolutionary genomic variations. AGB is now available at http://bioinfo.konkuk.ac.kr/genomebrowser/.

• Journal of Microbiology and Biotechnology
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• v.32 no.2
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• pp.149-159
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• 2022

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.