• Genomics & Informatics
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• v.17 no.3
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• pp.26.1-26.12
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• 2019

Identification of fusion gene is of prominent importance in cancer research field because of their potential as carcinogenic drivers. RNA sequencing (RNA-Seq) data have been the most useful source for identification of fusion transcripts. Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. We still lack a reliable program that achieves high precision with reasonable recall rate. Here, we present FusionScan, a highly optimized tool for predicting fusion transcripts from RNA-Seq data. We specifically search for split reads composed of intact exons at the fusion boundaries. Using 269 known fusion cases as the reference, we have implemented various mapping and filtering strategies to remove false-positives without discarding genuine fusions. In the performance test using three cell line datasets with validated fusion cases (NCI-H660, K562, and MCF-7), FusionScan outperformed other existing programs by a considerable margin, achieving the precision and recall rates of 60% and 79%, respectively. Simulation test also demonstrated that FusionScan recovered most of true positives without producing an overwhelming number of false-positives regardless of sequencing depth and read length. The computation time was comparable to other leading tools. We also provide several curative means to help users investigate the details of fusion candidates easily. We believe that FusionScan would be a reliable, efficient and convenient program for detecting fusion transcripts that meet the requirements in the clinical and experimental community. FusionScan is freely available at http://fusionscan.ewha.ac.kr/.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.127-141
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• 2016

With more emphasis on importance of software, many countries try to provide software education. Of course Korea includes informatics courses in 2015 revised curriculum, so that software education will be administered briskly in soon. However there are practical challenges including a lack of teaching hour in classes and the monotony of educational contents which occurs with that. To solve these problems, this research develop software education curriculum model that could be practically used for both middle and high school. First this study compare the curriculum of Korea to that of United States and United Kingdom. After analyzing the result, the curriculum model for middle and high school is developed. The curriculum model can be classified into three types, middle, high and advanced-high levels and include key concepts like collaboration and convergence, computational thinking, computing practice and programming, computers and communications devices, community, global, and ethical impacts. To assess the feasibility of our software education curriculum model, examination was made by expert group and a hearing was held by related researchers. Then the model was modified in a way that adjustable to Korea education system. This study provides some important guidances on designing a curriculum for software education at middle and high school. However, there still are difficulty adjusting to the elementary school and university course. To be able to further research, same kind of studies on elementary school and university course need to be done. Also, continuous modifications are required to reflect reality including technological advance, curriculum, and changes of education system.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.755-764
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• 2004

Recently, the rapid development of biotechnology brings the explosion of biological data and biological data host. Moreover, these data are highly distributed and heterogeneous, reflecting the distribution and heterogeneity of the Molecular Biology research community. As a consequence, the integration and interoperability of molecular biology databases are issue of considerable importance. But, up to now, most of the integrated systems such as link based system, data warehouse based system have many problems which are keeping the data up to date when the schema and data of the data source are changed. For this reason, the integrated system using web service technology that allow biological data to be fully exploited have been proposed. In this paper, we built the integrated system if the bio sequence information bated on the web service technology. The developed system allows users to get data with many format such as BSML, GenBank, Fasta to traverse disparate data resources. Also, it has better retrieval performance because the retrieval modules of the external database proceed in parallel.

• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.415-421
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• 2018

Objective: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in social skills and communication with repetitive behaviors. Etiology is still unclear although it is thought to develop with interaction of genes and environmental factors. Oxytocin has extensive effects on intrauterine brain development. Vitamin D, affects neural development and differentiation and contributes to the regulation of around 900 genes including oxytocin receptor gene. In the present study, the contribution of D vitamin receptor and oxytocin receptor gene polymorphisms in the development of ASD in Turkish community was investigated. To our knowledge, this is the first study examining these two associated genes together in the literature. Methods: Eighty-five patients diagnosed with ASD according to DSM-5 who were referred to outpatient clinics of Child and Adolescent Psychiatry of Başkent University and Mersin University and 52 healthy, age and gender-matched controls were included in the present study. Vitamin D receptor gene rs731236 (Taq1), rs2228570 (Fok1), rs1544410 (Bsm1), rs7975232 (Apa1) polymorphisms and oxytocin receptor gene rs1042778 and rs2268493 polymorphisms were investigated using real time polymerase chain reaction method. Results: No significant difference between groups in terms of distribution of genotype and alleles in each of polymorphisms for these genes could be found. Conclusion: Knowledge of genes and polymorphisms associated with the development of ASD may be beneficial for early diagnosis and future treatment. Further studies with larger populations are required to demonstrate molecular pathways which may play part in the development of ASD in Turkey.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.273-285
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• 2021

This study estimates the financial value of return on investment (ROI) of research funds. Four simulation estimations are employed to measure ROI finance value that considers the outputs, outcomes, impacts and total ROI from the allocation input received. Research outputs, outcomes, and impacts can be quantitatively measured based on improvements to existing systems. In terms of input, the Malaysian government has allocated MYR301,350,000 for fundamental research in the 2021 budget compared with 2019, up 9.5 percent from 2019. It brings up the question: To what extent does the input of research funds allocated by the government yield a good return in outputs, outcomes, and impacts to the academic community, society, and country? The result of total ROI shows around MYR7 return is generated by researchers for each Malaysian ringgit channeled by the funder. More specifically, for a research project, it is more difficult to produce impacts and outcomes compared to research outputs. The positive return is evidence that all the allocated funds are beneficial to the stakeholders. The government can apply this approach in calculating ROI for evaluation and fund allocation to universities. Furthermore, the positive financial value of research output, outcome, and impact automatically contribute to a positive innovation environment in Malaysia.

• Journal of the Health Care and Life Science
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• v.8 no.2
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• pp.135-142
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• 2020

The purpose of this study was to analyze the frequency of use of hospitalization/outpatient care of patients with addresses in Yeongbuk-gu, Gangwon-do to identify the medical demand and status of medical use in Yeongbuk-do. The National Health Insurance Corporation (www.data.go.kr) conducted an analysis of health insurance and medical benefits (inpatient/outpatient) claims data from 2003 to 2017. The order of the highest frequency of chronic disease was ranked from 1st to 60th according to 'Healing Case and %'. In addition, the use of patients at Sokcho Medical Center, the only hospital in the Yeongbuk region, was analyzed at the same time. According to the analysis, the use of outpatient treatment and In-patients in the Yeongbuk area of Gangwon-do is increasing due to chronic non-infectious diseases from the past acute diseases. In particular, it is necessary to expand the functions of schizophrenia and obstetrics and gynecology and to carry out specific health projects necessary for the health care of the local community. Through this, we should improve the quality of life in Yeongbuk, Gangwon Province.

• Genomics & Informatics
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• v.19 no.4
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• pp.49.1-49.11
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• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• The Journal of Bigdata
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• v.6 no.2
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• pp.99-108
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• 2021

Recently, unexpected and more advanced cyber medical treat attacks are on the rise. However, in responding to various patterns of cyber medical threat attack, rule-based security methodologies such as physical blocking and replacement of medical devices have the limitations such as lack of the man-power and high cost. As a way to solve the problems, the medical community is also paying attention to artificial intelligence technology that enables security threat detection and prediction by self-learning the past abnormal behaviors. In this study, there has collecting and learning the medical information data from integrated Medical-Information-Systems of the medical center and introduce the research methodology which is to develop the AI-based Net-Working Behavior Adaptive Information data. By doing this study, we will introduce all technological matters of rule-based security programs and discuss strategies to activate artificial intelligence technology in the medical information business with the various restrictions.

• Genomics & Informatics
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• v.21 no.4
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• pp.50.1-50.9
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• 2023

Vaccine development is one of the key efforts to control the spread of coronavirus disease 2019 (COVID-19). However, it has become apparent that the immunity acquired through vaccination is not permanent, known as the waning effect. Therefore, monitoring the proportion of the population with immunity is essential to improve the forecasting of future waves of the pandemic. Despite this, the impact of the waning effect on forecasting accuracies has not been extensively studied. We proposed a method for the estimation of the effective immunity (EI) rate which represents the waning effect by integrating the second and booster doses of COVID-19 vaccines. The EI rate, with different periods to the onset of the waning effect, was incorporated into three statistical models and two machine learning models. Stringency Index, omicron variant BA.5 rate (BA.5 rate), booster shot rate (BSR), and the EI rate were used as covariates and the best covariate combination was selected using prediction error. Among the prediction results, Generalized Additive Model showed the best improvement (decreasing 86% test error) with the EI rate. Furthermore, we confirmed that South Korea's decision to recommend booster shots after 90 days is reasonable since the waning effect onsets 90 days after the last dose of vaccine which improves the prediction of confirmed cases and deaths. Substituting BSR with EI rate in statistical models not only results in better predictions but also makes it possible to forecast a potential wave and help the local community react proactively to a rapid increase in confirmed cases.

• The Korean Journal of Pain
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• v.37 no.1
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• pp.41-50
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• 2024

Background: Recognizing the seriousness of the misuse and abuse of medical narcotics, the South Korean government introduced the world's first narcotic management system, the Narcotics Information Management System (NIMS). This study aimed to explore the recent one-year opioid prescribing patterns in South Korea using the NIMS database. Methods: This study analyzed opioid prescription records in South Korea for the year 2022, utilizing the dispensing/administration dataset provided by NIMS. Public data from the Korean Statistical Information Service were also utilized to explore prescription trends over the past four years. The examination covered 16 different opioid analgesics, assessed by the total number of units prescribed based on routes of administration, type of institutions, and patients' sex and age group. Additionally, the disposal rate for each ingredient was computed. Results: In total, 206,941 records of 87,792,968 opioid analgesic units were analyzed. Recently, the overall quantity of prescribed opioid analgesic units has remained relatively stable. The most prescribed ingredient was oral oxycodone, followed by tapentadol and sublingual fentanyl. Tertiary hospitals had the highest number of dispensed units (49.4%), followed by community pharmacies (40.2%). The highest number of prescribed units was attributed to male patients in their 60s. The disposal rates of the oral and transdermal formulations were less than 0.1%. Conclusions: Opioid prescription in South Korea features a high proportion of oral formulations, tertiary hospital administration, pharmacy dispensing, and elderly patients. Sustained education and surveillance of patients and healthcare providers is required.