• Korean Journal of Clinical Laboratory Science
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• v.44 no.4
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• pp.167-177
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• 2012

Next-Generation Sequencing (NGS) is a term that means post-Sanger sequencing methods with high-throughput sequencing technologies. NGS parallelizes the sequencing process, producing thousands or millions of sequences at once. The latest NGS technologies use even single DNA molecule as a template and measures the DNA sequence directly via measuring electronic signals from the extension or degradation of DNA. NGS is making big impacts on biomedical research, molecular diagnosis and personalized medicine. The hospitals are rapidly adopting the use of NGS to help to patients understand treatment with sequencing data. As NGS equipments are getting smaller and affordable, many hospitals are in the process of setting up NGS platforms. In this review, the progress of NGS technology development and action mechanisms of representative NGS equipments of each generation were discussed. The key technological advances in the commercialized platforms were presented. As NGS platforms are a great concern in the healthcare area, the latest trend in the use of NGS and the prospect of NGS in the future in diagnosis and personalized medicine were also discussed.

• Journal of Life Science
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• v.25 no.3
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• pp.357-367
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• 2015

With the ongoing development of next-generation sequencing (NGS) platforms and advancements in the latest bioinformatics tools at an unprecedented pace, the ultimate goal of sequencing the human genome for less than $1,000 can be feasible in the near future. The rapid technological advances in NGS have brought about increasing demands for statistical methods and bioinformatics tools for the analysis and management of NGS data. Even in the early stages of the commercial availability of NGS platforms, a large number of applications or tools already existed for analyzing, interpreting, and visualizing NGS data. However, the availability of this plethora of NGS data presents a significant challenge for storage, analyses, and data management. Intrinsically, the analysis of NGS data includes the alignment of sequence reads to a reference, base-calling, and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection, and genome browsing. While the NGS technologies have allowed a massive increase in available raw sequence data, a number of new informatics challenges and difficulties must be addressed to improve the current state and fulfill the promise of genome research. This review aims to provide an overview of major NGS technologies and bioinformatics tools for NGS data analyses.

• The Korean Journal of Blood Transfusion
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• v.29 no.3
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• pp.310-319
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• 2018

Background: Research on next-generation sequencing (NGS)-based HLA typing is active. To resolve the phase ambiguity and long turn-around-time of conventional high resolution HLA typing, this study developed a NGS-based high resolution HLA typing method that can handle large-scale samples within an efficient testing time. Methods: For HLA NGS, the condition of nucleic acid extraction, library construction, PCR mechanism, and HLA typing with bioinformatics were developed. To confirm the accuracy of the NGS-based HLA typing method, the results of 192 samples HLA typed by SSOP and 28 samples typed by SBT compared to NGS-based HLA-A, -B and -DR typing. Results: DNA library construction through two-step PCR, NGS sequencing with MiSeq (Illumina Inc., San Diego, USA), and the data analysis platform were established. NGS-based HLA typing results were compatible with known HLA types from 220 blood samples. Conclusion: The NSG-based HLA typing method could handle large volume samples with high-throughput. Therefore, it would be useful for HLA typing of bone marrow donation volunteers.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.257-264
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• 2021

In this study, we analyzed the food components in the release product that sampled Sinonovacula constricta from the foreshore littoral at Byeongnyang-myeon, Suncheon Bay. We used microscopy and next-generation sequencing (NGS) to evaluate the applicability of morphological and molecular methods to analyze release products. The higher species diversity observed in the NGS method is due to the different levels of species identification, as microscopy displays morphological and anatomical levels of plankton species identification in S. constrita. Moreover, NGS can identify the level of species in the organic matter by using the 18s_V9 primer.

• Journal of Life Science
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• v.31 no.4
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• pp.410-417
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• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.107-112
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• 2013

With the progress of NGS technologies, large genome data have been exploded recently. To analyze such data effectively, the assistance of HPC technique is necessary. In this paper, we organized a genome analysis pipeline to call SNP from NGS data. To organize the pipeline efficiently under HPC environment, we analyzed the CPU utilization pattern of each pipeline steps. We found that sequence alignment is computing centric and suitable for parallelization. We also analyzed the performance of parallel open source alignment tools and found that alignment method utilizing many-core processor can improve the performance of genome analysis pipeline.

• Journal of Life Science
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• v.24 no.11
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• pp.1258-1267
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• 2014

Developing economic traits with a high growth rate, robustness, and disease resistance in livestock is an important challenge. RFLP and AFLP are the classical methods used to develop economic traits. Whole-genome-based economic traits have recently been detected with the advent of next-generation sequencing (NGS) technologies. However, NGS technologies are rather costly for use in studies, and RNA-seq, RAD-Seq, RRL, MSG, and GBS have been used to overcome the issue of high costs. In this study, recent NGS-based studies were reviewed, particularly those that focused on minimum costs and maximum effects. Then, we presented further prospects on how to apply for selection of high economic-trait livestock.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.796-799
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• 2009

NGS(Next Generation Storage) 시스템은 전형적인 분산파일 시스템 구조의 병목 현상을 제거하고 입출력 대역폭을 늘려 성능을 최대화 하기 위한 차세대 저장시스템으로 기존의 저장시스템과는 달리 DRAM을 기반으로 스토리지를 구성하고 있다. NGS 시스템의 대용량 지원 및 기업 내부에서의 활용을 위해서는 SAN 기반에서 활용할 수 있도록 설계되어야 하며, SAN 환경에서 성능 향상을 위한 연구가 필요하다. 본 논문에서는 NGS 시스템에 대한 성능평가 및 분산 환경에서 NGS 를 활용하기 위한 성능평가도구 개발을 기술한다. 성능 도구의 활용은 전형적인 전체 시스템 아키텍처 내의 병목 현상을 제거하고 입출력 대역폭을 늘려 성능을 최대화 할 수 있어야 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.25-27
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• 2012

디노버 어셈블리는 레퍼런스 시퀀스 없이 리드의 염기 서열 정보를 이용하여 원래의 전체 시퀀스(original sequence)로 추정되는 시퀀스로 리드들을 재구성하는 방식이다. 최근의 NGS(Next Generation Sequencing) 기술은 대용량 리드를 훨씬 쉽게 저비용으로 생성할 수 있다는 장점이 있어, 이를 이용한 많은 연구가 이루어지고 있다. 그러나 NGS 리드 데이터를 이용한 디노버 어셈블리에 관한 연구는 국내외적으로 매우 미흡한 실정이다. 그 이유는 NGS 리드 데이터를 이용하여 디노버 어셈블리를 수행하는 경우 대용량 데이터, 복잡한 데이터 구조 및 처리 과정 등으로 인하여 매우 많은 시간과 공간이 소요될 뿐만 아니라 아직까지 다양한 분석 툴과 노하우 등이 충분히 개발되어 있지 않기 때문이다. 본 연구에서는 NGS 리드 데이터를 이용한 어셈블리의 실효성과 정확성을 검증한다. 또한 디노버 어셈블리의 처리 시간 및 공간 오버헤드를 해결하기 위하여 유사 종과의 리드 정렬을 활용하는 방안을 제안한다.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.1
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• pp.3-12
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• 2022

Selection of potential disease-specific biomarkers from saliva or epithelial tissues through next generation sequencing (NGS)-based protein studies has recently become possible. The early diagnosis of oral squamous cell carcinoma (OSCC) has been difficult, if not impossible, until now due to the lack of an effective OSCC biomarker and efficient molecular validation method. The aim of this study was to summarize the advances in the application of NGS in cancer research and to propose potential proteomic and genomic saliva biomarkers for NGS-based study in OSCC screening and diagnosis programs. We have reviewed four categories including definitions and use of NGS, salivary biomarkers and OSCC, current biomarkers using the NGS-based technique, and potential salivary biomarker candidates in OSCC using NGS.