• Journal of Microbiology and Biotechnology
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• v.25 no.6
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• pp.765-770
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• 2015

Recent sequencing technology development has revolutionized fields of microbial ecology. MiSeq-based microbial community analysis allows us to sequence more than a few hundred samples at a time, which is far more cost-effective than pyrosequencing. The approach, however, has not been preferably used owing to computational difficulties of processing huge amounts of data as well as known Illumina-derived artefact problems with amplicon sequencing. The choice of assembly software to take advantage of paired-end sequencing and methods to remove Illumina artefacts sequences are discussed. The protocol we suggest not only removed erroneous reads, but also dramatically reduced computational workload, which allows even a typical desktop computer to process a huge amount of sequence data generated with Illumina sequencers. We also developed a Web interface (http://biotech.jejunu.ac.kr/ ~abl/16s/) that allows users to conduct fastq-merging and mothur batch creation. The study presented here should provide technical advantages and supports in applying MiSeq-based microbial community analysis.

• International Journal of Oral Biology
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• v.45 no.3
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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.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.155-164
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• 1996

Biomass to methane via anaerobic digestion conversion is a good supply method of substitutable energy resources. The economic viability of this technology is contingent upon managing the production facilities in a cost effective manner. The problem is to determine the batch production sequence as well as the batch residence times in the digester so as to maximize total gas production over a given planning horizon. The problem is difficult to solve since the batch sequencing decisions and the batch residence time decisions cannot be isolated. This paper developes a heuristic algorithm which is based on a dynamic programming procedure for the multiple feedstock sequencing and scheduling biogas production systems and demonstrates to yield good results.

• Genomics & Informatics
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• v.6 no.2
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• pp.87-90
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• 2008

During the last four years, the pyrosequencing-based 454 platform has rapidly displaced the traditional Sanger sequencing method due to its high throughput and cost effectiveness. Meanwhile, the Sanger sequencing methodology still provides the longest reads, and paired-end sequencing that is based on that chemistry offers an opportunity to ensure accurate assembly results. In this report, we describe an optimized approach for hybrid de novo genome assembly using pyrosequencing data and varying amounts of Sanger-type reads. 454 platform-derived contigs can be used as single non-breakable virtual reads or converted to simpler contigs that consist of editable, overlapping pseudoreads. These modified contigs maintain their integrity at the first jumpstarting assembly stage and are edited by fragmenting and rejoining. Pre-existing assembly software then can be applied for mixed assembly with 454-derived data and Sanger reads. An effective method for identifying genomic differences between reference and sample sequences in whole-genome resequencing procedures also is suggested.

• Genomics & Informatics
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• v.11 no.4
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• pp.191-199
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• 2013

High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.

• Environmental Engineering Research
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• v.11 no.2
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• pp.63-76
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• 2006

Multivariate analysis and batch monitoring on a pilot-scale sequencing batch reactor (SBR) are described for integrated wastewater treatment management system, where a batchwise multiway independent component analysis method (MICA) are used to extract meaningful hidden information from non-Gaussian wastewater treatment data. Three-way batch data of SBR are unfolded batch-wisely, and then a non-Gaussian multivariate monitoring method is used to capture the non-Gaussian characteristics of normal batches in biological wastewater treatment plant. It is successfully applied to an 80L SBR for biological wastewater treatment, which is characterized by a variety of error sources with non-Gaussian characteristics. The batchwise multivariate monitoring results of a pilot-scale SBR for integrated wastewater treatment management system showed more powerful monitoring performance on a WWTP application than the conventional method since it can extract non-Gaussian source signals which are independent and cross-correlation of variables.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.2
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• pp.158-165
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• 2015

Marbling is an important trait regarding the quality of beef. Analysis of beef cattle transcriptome and its expression profile data are essential to extend the genetic information resources and would support further studies on beef cattle. RNA sequencing was performed in beef cattle using the Illumina High-Seq2000 platform. Approximately 251.58 million clean reads were generated from a high marbling (H) group and low marbling (L) group. Approximately 80.12% of the 19,994 bovine genes (protein coding) were detected in all samples, and 749 genes exhibited differential expression between the H and L groups based on fold change (>1.5-fold, p<0.05). Multiple gene ontology terms and biological pathways were found significantly enriched among the differentially expressed genes. The transcriptome data will facilitate future functional studies on marbling formation in beef cattle and may be applied to improve breeding programs for cattle and closely related mammals.

• Plant Breeding and Biotechnology
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• v.5 no.4
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• pp.269-281
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• 2017

With the continual development of genetically modified (GM) crops, it has become necessary to develop detailed and effective molecular characterization methods to select candidate events from a large pool of transformation events. Relative to traditional molecular analysis methods such as the polymerase chain reaction (PCR) and Southern blot hybridization, next generation sequencing (NGS) technology for whole-genome sequencing of complex crop genomes had proven comparatively useful for in-depth molecular characterization. In this study, four transformation events, including one in Bacillus thuringiensis (Bt)-resistant rice, one in resveratrol-producing rice, and two in beta-carotene-enhanced soybeans, were selected for molecular characterization. To merge NGS analysis and Southern blot-hybridization results, we confirmed the transgene insertion sites, insertion construction, and insertion numbers of these four transformation events. In addition, the read-coverage depth assessed by NGS analysis for inserted genes might provide consistent results in terms of inserted T-DNA numbers in case of complex insertion structures and highly duplicated donor genomes; however, PCR-based methods can produce incorrect conclusions. Our combined method provides an effective and complete analytical approach for whole-genome visual inspection of transformation events that require biosafety assessment.

• BMB Reports
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• v.55 no.3
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• pp.113-124
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• 2022

Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

• Proceedings of the Microbiological Society of Korea Conference
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• 2009.05a
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• pp.169-170
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• 2009