• Journal of the military operations research society of Korea
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• v.29 no.2
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• pp.61-80
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• 2003

A fire sequencing problem is considered. Fire sequencing problem is a kind of scheduling problem that seeks to minimize the overall time span under a result of weapon­target allocation problem. The assigned weapons should impact a target simultaneously and a weapon cannot transfer the firing against another target before all planned rounds are consumed. The computational complexity of the fire sequencing problem is strongly NP­complete even if the number of weapons is two, so it is difficult to get the optimal solution in a reasonable time by the mathematical programming approach. Therefore, a genetic algorithm is adopted as a solution method, in which the representation of the solution, crossover and mutation strategies are applied on a specific condition. Computational results using randomly generated data are presented. We compared the solutions given by CPLEX and the genetic algorithm. Above $7(weapon){\times}15(target)$ size problems, CPLEX could not solve the problem even if we take enough time to solve the problem since the required memory size increases dramatically as the number of nodes expands. On the other hand, genetic algorithm approach solves all experimental problems very quickly and gives good solution quality.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.1
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• pp.47-65
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• 2010

In this study the artillery fire system is investigated in consideration of the characteristics of the troop and the target. Two kinds of decision are to be made on the target allocation with fire ammunition and the fire sequencing for the target with duties in charge. The objective is to minimize the completion time for all troops. Each target has the specified amount of load of fire, which can be accomplished by a single troop or the combination of the troops having different capabilities. Mathematical model is suggested, and the heuristic algorithm which yields a solution within a reasonable computation time is developed. The algorithm consists of iterative three steps : the initial solution generation, the division improvement, and the exchange improvement. The performance of the heuristic is evaluated through the computational experiment

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.2
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• pp.360-372
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• 2020

Objective: Specific genomic sites can be recognized and permanently modified by genome editing. The discovery of endonucleases has advanced genome editing in pigs, attenuating xenograft rejection and cross-species disease transmission. However, off-target mutagenesis caused by these nucleases is a major barrier to putative clinical applications. Furthermore, off-target mutagenesis by genome editing has not yet been addressed in pigs. Methods: Here, we generated genetically inheritable α-1,3-galactosyltransferase (GGTA1) knockout Yucatan miniature pigs by combining transcription activator-like effector nuclease (TALEN) and nuclear transfer. For precise estimation of genomic mutations induced by TALEN in GGTA1 knockout pigs, we obtained the whole-genome sequence of the donor cells for use as an internal control genome. Results: In-depth whole-genome sequencing analysis demonstrated that TALEN-mediated GGTA1 knockout pigs had a comparable mutation rate to homologous recombination-treated pigs and wild-type strain controls. RNA sequencing analysis associated with genomic mutations revealed that TALEN-induced off-target mutations had no discernable effect on RNA transcript abundance. Conclusion: Therefore, TALEN appears to be a precise and safe tool for generating genomeedited pigs, and the TALEN-mediated GGTA1 knockout Yucatan miniature pigs produced in this study can serve as a safe and effective organ and tissue resource for clinical applications.

• Genomics & Informatics
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• v.12 no.2
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• pp.50-57
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• 2014

We present a new next-generation sequencing-based method to identify somatic mutations of lung cancer. It is a comprehensive mutation profiling protocol to detect somatic mutations in 30 genes found frequently in lung adenocarcinoma. The total length of the target regions is 107 kb, and a capture assay was designed to cover 99% of it. This method exhibited about 97% mean coverage at $30{\times}$ sequencing depth and 42% average specificity when sequencing of more than 3.25 Gb was carried out for the normal sample. We discovered 513 variations from targeted exome sequencing of lung cancer cells, which is 3.9-fold higher than in the normal sample. The variations in cancer cells included previously reported somatic mutations in the COSMIC database, such as variations in TP53, KRAS, and STK11 of sample H-23 and in EGFR of sample H-1650, especially with more than $1,000{\times}$ coverage. Among the somatic mutations, up to 91% of single nucleotide polymorphisms from the two cancer samples were validated by DNA microarray-based genotyping. Our results demonstrated the feasibility of high-throughput mutation profiling with lung adenocarcinoma samples, and the profiling method can be used as a robust and effective protocol for somatic variant screening.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8035-8040
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• 2014

Gastric cancer is the second after lung cause of cancer-related mortality in the world. Early detection and treatment can lead to a long survival time. Recently microarrays and next generation sequencing (NGS) have become very useful tools of comprehensive research into gastric cancer, facilitating the identification of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discovery to practical clinical benefits. Although there are many biomarkers and target agents, only a minority of patients are tested and treated accordingly. Microarray technology with maturity was established more than 10 years ago, and has been widely used in the study of functional genomics, systems biology, and genomes in medicine. Second generation sequencing technology is more recent, but development is very fast, and it has been applied to the genome, including sequencing and epigenetics and many aspects of functional genomics. Here we review insights gained from these studies regarding the technology of microarray and NGS, how to elucidate the molecular basis of gastric cancer and identify potential therapeutic targets, and how to analyse candidate genes. We also discuss the challenges and future directions of such efforts.

• Genomics & Informatics
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• v.15 no.4
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• pp.136-141
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• 2017

Accurate detection of genomic alterations, especially druggable hotspot mutations in tumors, has become an essential part of precision medicine. With targeted sequencing, we can obtain deeper coverage of reads and handle data more easily with a relatively lower cost and less time than whole-exome or whole-genome sequencing. Recently, we designed a customized gene panel for targeted sequencing of major solid cancers. In this study, we aimed to validate its performance. The cancer panel targets 95 cancer-related genes. In terms of the limit of detection, more than 86% of target mutations with a mutant allele frequency (MAF) <1% can be identified, and any mutation with >3% MAF can be detected. When we applied this system for the analysis of Acrometrix Oncology Hotspot Control DNA, which contains more than 500 COSMIC mutations across 53 genes, 99% of the expected mutations were robustly detected. We also confirmed the high reproducibility of the detection of mutations in multiple independent analyses. When we explored copy number alterations (CNAs), the expected CNAs were successfully detected, and this result was confirmed by target-specific genomic quantitative polymerase chain reaction. Taken together, these results support the reliability and accuracy of our cancer panel in detecting mutations. This panel could be useful for key mutation profiling research in solid tumors and clinical translation.

• BMB Reports
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• v.54 no.7
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• pp.386-391
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• 2021

Owing to rapid advancements in NGS (next generation sequencing), genomic alteration is now considered an essential predictive biomarkers that impact the treatment decision in many cases of cancer. Among the various predictive biomarkers, tumor mutation burden (TMB) was identified by NGS and was considered to be useful in predicting a clinical response in cancer cases treated by immunotherapy. In this study, we directly compared the lab-developed-test (LDT) results by target sequencing panel, K-MASTER panel v3.0 and whole-exome sequencing (WES) to evaluate the concordance of TMB. As an initial step, the reference materials (n = 3) with known TMB status were used as an exploratory test. To validate and evaluate TMB, we used one hundred samples that were acquired from surgically resected tissues of non-small cell lung cancer (NSCLC) patients. The TMB of each sample was tested by using both LDT and WES methods, which extracted the DNA from samples at the same time. In addition, we evaluated the impact of capture region, which might lead to different values of TMB; the evaluation of capture region was based on the size of NGS and target sequencing panels. In this pilot study, TMB was evaluated by LDT and WES by using duplicated reference samples; the results of TMB showed high concordance rate (R² = 0.887). This was also reflected in clinical samples (n = 100), which showed R² of 0.71. The difference between the coding sequence ratio (3.49%) and the ratio of mutations (4.8%) indicated that the LDT panel identified a relatively higher number of mutations. It was feasible to calculate TMB with LDT panel, which can be useful in clinical practice. Furthermore, a customized approach must be developed for calculating TMB, which differs according to cancer types and specific clinical settings.

• Journal of Life Science
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• v.11 no.1
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• pp.19-23
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• 2001

To develop the effective microbial screening method, pyrolysis mass spectrometry (PyMS) fingerprinting was evaluated as a tool that discriminate various yeast strains. The target yeast strains were isolated from industrial wastewater. Seventeen environmental isolated yeast strains were examined by pyrolysis mass spectrometry and sequencing analysis of the large subunit rRNA gene D1/D2 region. The PyMS results were compared with those of sequencing analysis. Taxonomic correlations were observed between the PyMS data and the sequencing results. It was concluded that PyMS provides a rapid, reliable and cost-reducing method for discrimination of the yeast strains.

• 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.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.105-115
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• 2007

It is essential to give a fatal damage to the enemy force by using prompt and accurate fire in order to overcome the lack of artillery force. During the artillery fire operations, minimizing the firing time will secure the adapt ability in tactical operation. In this paper, we developed a mathematical model to schedule the artillery fire on the multiple targets to decrease total fire operation time. To design a program to describe a real firing situation, we consider many possible circumstances of changes such as commander's intention, firing constraints, target priority, and contingency plan to make a fire plan in an artillery unit. In order to work out the target sequencing problem, MIP is developed and the optimum solution is obtained by using ILOG OPL. If this analytical model is applied to a field artillery unit, it will improve the efficiency of the artillery fire force operations.