• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.3009-3015
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• 2013

Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer and method of the most fundamental being determining an individual's genotype from multiple aligned short read sequences at a position. Bayesian algorithm estimate parameter using posterior genotype probabilities and other method, EM algorithm, estimate parameter using maximum likelihood estimate method in observed data. Here, we propose a novel genotype-calling system and compare and analyze the effect of sample size(S = 50, 100 and 500) on posterior estimate of sequencing error rate, somatic mutation status and genotype probability. The result is that estimate applying Bayesian algorithm even for 50 of small sample size approached real parameter than estimate applying EM algorithm in small sample more accurately.

• The Korean Journal of Cytopathology
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• v.8 no.1
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• pp.83-86
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• 1997

Signet ring cell carcinoma is a variant of adenocarcinoma and has been rarely reported in the lung as a primary site. Recently, we experienced two cases of primary signet ring cell carcinoma in the lung without any other extrapulmonary lesion. Sputum cytology was performed and the tumor cells which have eccentrically located nuclei and abundnat mucinous cytoplasm were dispersed in diffuse sheets. On resected specimen, the signet ring cells occupied about $50{\sim}80%$ of all tumor cell nests. Histochemical staining revealed that the mucin produced by tumor cells was mostly carboxylated acid mucins. Ultrastructurally, the tumor cells contained variable sized membrane-bound mucin granules with weak central osmilophilic density and showed numerous surface microvilli, which represented that tumor cells arose from bronchial epithelial cells. In general, this tumor has diffusely infiltrative nature and the prognosis is fatal due to widespread metastasis before clinical discovery.

• Animal cells and systems
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• v.3 no.1
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• pp.1-7
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• 1999

Gonadotropin-releasing hormone (GnRH) was originally isolated as a hypothalamic peptide that regulates reproduction by stimulating the release of gonadotropins. Using comparative animal models has led to the discovery that GnRH has a more ancient evolutionary origin. Durinq evolution GnRH peptide underwent gene duplication and structural changes to give rise to multiple molecular forms of GnRHs. Mammalian GnRH initially considered to be the sole molecular form, is now grouped as a family of peptides along with GnRH variants determined from representatives in all classes of vertebrates. Vertebrate species including primates and humanshave more than one GnRH variant in individual brains; a unique GnRH form in the forebrain and chicken IIGnRH in the midbrain. Furthermore, several species of bony fish have three molecular variants of GnRH: salmon GnRH sea-bream GnRH and chicken II GnRH. Also, it has been shown that in addition to the olfactory placodes and the midbrain, there is a third embryonic source of GnRH neurons from the basal diencephalon in birds and fish, which might be true for other vertebrates. Therefore, comparative animal models like fish with discrete sites of expression of three molecular variants of GnRH in individual brains, could provide insight into novel functions of GnRH variants, conservation of gene regulation, and mechanisms governing reproduction in vertebrates.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.73-82
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• 2000

This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

• Genomics & Informatics
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• v.20 no.1
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• pp.5.1-5.10
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• 2022

Non-syndromic hearing loss (NSHL) is a common hereditary disorder. Both clinical and genetic heterogeneity has created many obstacles to understanding the causes of NSHL. The present study has attempted to ravel the genetic aetiology in NSHL progression and to screen out potential target genes using computational approaches. The reported NSHL target genes (2009-2020) have been studied by analyzing different biochemical and signaling pathways, interpretation of their functional association network, and discovery of important regulatory interactions with three previously established miRNAs in the human inner ear as well as in NSHL such as miR-183, miR-182, and miR-96. This study has identified SMAD4 and SNAI2 as the most putative target genes of NSHL. But pathogenic and deleterious non-synonymous single nucleotide polymorphisms discovered within SMAD4 is anticipated to have an impact on NSHL progression. Additionally, the identified deleterious variants in the functional domains of SMAD4 added a supportive clue for further study. Thus, the identified deleterious variant i.e., rs377767367 (G491V) in SMAD4 needs further clinical validation. The present outcomes would provide insights into the genetics of NSHL progression.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.34-34
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• 2022

Capacity building for bioinformatics could be achieved with the systematic training of research staff and higher degree students in the current best practices for analysis of data from 'omic-type experiments. It is anticipated that the KOICA-University of the Philippines Los Baños - International Rice Research Insitute Agricultural Genomics Research Center activities will focus on the use of next generation sequencing technology for genome sequencing and annotation, genome variant discovery for use in GWAS and QTL mapping, and transcriptome analysis of organisms important to agriculture and food security. Such activities require that researchers have high levels of knowledge and skills in bioinformatics in order to gain insights from the results of the experiments performed. In this talk the bioinformatic tools/solutions and online training materials already available will be presented, as well the upcoming resources under development in support of the project.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Clinical and Experimental Pediatrics
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• v.60 no.9
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• pp.282-289
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• 2017

Purpose: Recent advancements in molecular techniques have greatly contributed to the discovery of genetic causes of unexplained developmental delay. Here, we describe the results of array comparative genomic hybridization (CGH) and the clinical features of 27 patients with global developmental delay. Methods: We included 27 children who fulfilled the following criteria: Korean children under 6 years with global developmental delay; children who had at least one or more physical or neurological problem other than global developmental delay; and patients in whom both array CGH and G-banded karyotyping tests were performed. Results: Fifteen male and 12 female patients with a mean age of $29.3{\pm}17.6months$ were included. The most common physical and neurological abnormalities were facial dysmorphism (n=16), epilepsy (n=7), and hypotonia (n=7). Pathogenic copy number variation results were observed in 4 patients (14.8%): 18.73 Mb dup(2)(p24.2p25.3) and 1.62 Mb del(20p13) (patient 1); 22.31 Mb dup(2) (p22.3p25.1) and 4.01 Mb dup(2)(p21p22.1) (patient 2); 12.08 Mb del(4)(q22.1q24) (patient 3); and 1.19 Mb del(1)(q21.1) (patient 4). One patient (3.7%) displayed a variant of uncertain significance. Four patients (14.8%) displayed discordance between G-banded karyotyping and array CGH results. Among patients with normal array CGH results, 4 (16%) revealed brain anomalies such as schizencephaly and hydranencephaly. One patient was diagnosed with Rett syndrome and one with $M{\ddot{o}}bius$ syndrome. Conclusion: As chromosomal microarray can elucidate the cause of previously unexplained developmental delay, it should be considered as a first-tier cytogenetic diagnostic test for children with unexplained developmental delay.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.9
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• pp.1353-1362
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• 2016

Hanwoo, a Korean native cattle (Bos taurus coreana), has great economic value due to high meat quality. Also, the breed has genetic variations that are associated with production traits such as health, disease resistance, reproduction, growth as well as carcass quality. In this study, next generation sequencing technologies and the availability of an appropriate reference genome were applied to discover a large amount of single nucleotide polymorphisms (SNPs) in ten Hanwoo bulls. Analysis of whole-genome resequencing generated a total of 26.5 Gb data, of which 594,716,859 and 592,990,750 reads covered 98.73% and 93.79% of the bovine reference genomes of UMD 3.1 and Btau 4.6.1, respectively. In total, 2,473,884 and 2,402,997 putative SNPs were discovered, of which 1,095,922 (44.3%) and 982,674 (40.9%) novel SNPs were discovered against UMD3.1 and Btau 4.6.1, respectively. Among the SNPs, the 46,301 (UMD 3.1) and 28,613 SNPs (Btau 4.6.1) that were identified as Hanwoo-specific SNPs were included in the functional genes that may be involved in the mechanisms of milk production, tenderness, juiciness, marbling of Hanwoo beef and yellow hair. Most of the Hanwoo-specific SNPs were identified in the promoter region, suggesting that the SNPs influence differential expression of the regulated genes relative to the relevant traits. In particular, the non-synonymous (ns) SNPs found in CORIN, which is a negative regulator of Agouti, might be a causal variant to determine yellow hair of Hanwoo. Our results will provide abundant genetic sources of variation to characterize Hanwoo genetics and for subsequent breeding.

• Genomics & Informatics
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• v.12 no.4
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• pp.195-202
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• 2014

Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, $52.2{\pm}8.9years$ ; body mass index, $24.6{\pm}3.2kg/m^2$). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < $5{\times}10^{-6}$), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < $1.38{\times}10^{-7}$, Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.