• Genomics & Informatics
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• 제8권3호
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• pp.131-137
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• 2010

Genome-wide association studies (GWASs) have greatly contributed to the identification of common variants responsible for numerous complex traits. There are, however, unavoidable limitations in detecting causal and/or rare variants for traits in this approach, which depends on an LD-based tagging SNP microarray chip. In an effort to detect potential casual and/or rare variants for complex traits, such as type 2 diabetes (T2D) and triglycerides (TGs), we conducted a targeted resequencing of loci identified by the Korea Association REsource (KARE) GWAS. The target regions for resequencing comprised whole exons, exon-intron boundaries, and regulatory regions of genes that appeared within 1 Mb of the GWA signal boundary. From 124 individuals selected in population-based cohorts, a total of 0.7 Mb target regions were captured by the NimbleGen sequence capture 385K array. Subsequent sequencing, carried out by the Roche 454 Genome Sequencer FLX, generated about 110,000 sequence reads per individual. Mapping of sequence reads to the human reference genome was performed using the SSAHA2 program. An average of 62.2% of total reads was mapped to targets with an average 22X-fold coverage. A total of 5,983 SNPs (average 846 SNPs per individual) were called and annotated by GATK software, with 96.5% accuracy that was estimated by comparison with Affymetrix 5.0 genotyped data in identical individuals. About 51% of total SNPs were singletons that can be considered possible rare variants in the population. Among SNPs that appeared in exons, which occupies about 20% of total SNPs, 304 nonsynonymous singletons were tested with Polyphen to predict the protein damage caused by mutation. In total, we were able to detect 9 and 6 potentially functional rare SNPs for T2D and triglycerides, respectively, evoking a further step of replication genotyping in independent populations to prove their bona fide relevance to traits.

• 지능정보연구
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• 제16권3호
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• pp.1-14
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• 2010

역전파 알고리즘은 오랫동안 부도예측모형 관련한 연구에 많이 적용되어왔다. 역전파 알고리즘을 사용하기전에 필히 고려해야 할 중요한 요소들로는 네트워크 구조, 학습요소, 정규화 방법 등이다. 하지만 신경망 성과를 향상시키기 위한 네트워크 구조 및 학습요소 최적화 관련한 연구는 기존의 연구들에서 많이 이루어 졌지만 데이터 정규화와 관련한 연구는 아직 많이 이루어지지 않았다. 따라서 본 연구에서는 유전자 알고리즘을 기반으로 하는 정규화 기법을 제시하였다. 최적의 입력데이터 정규화를 위하여 본 연구에서는 우선 각각의 서로 다른 정규화 기법들을 동일 가중치를 두어 일반화 시켰으며 유전자 알고리즘을 이용하여 최적의 가중치를 찾음으로써 최적화된 입력변수 정규화가 이루어지도록 하였다. 제안한 방법론을 검증하기 위하여 부도예측 데이터를 이용하여 실험을 하였으며 제안하는 방법과 기존 다른 방법들간의 비교를 통하여 그 타당성을 검증하였다.

• The Plant Pathology Journal
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• 제36권6호
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• pp.558-569
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• 2020

Fusarium head blight (FHB) is a devastating fungal disease of wheat (Triticum aestivum L.). The lack of genetic resources with stable FHB resistance combined with a reliable and rapid screening method to evaluate FHB resistance is a major limitation to the development of FHB resistant wheat germplasm. The present study utilized an immature wheat spike culture method to screen wheat spike culture derived variants (SCDV) for FHB resistance. Mycotoxin concentrations determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) correlated significantly (P < 0.01) with FHB severity and disease progression during in vitro spike culture. Selected SCDV lines assessed for FHB resistance in a Fusarium field disease nursery in Carman, Manitoba, Canada in 2016 showed significant (P < 0.01) correlation of disease severity to the in vitro spike culture screening method. Selected resistant SCDV lines were also crossed with an elite cv. CDC Hughes and the progeny of F₂ and BC₁F₂ were screened by high resolution melt curve (HRM) analyses for the wheat UDP-glucosyl transferase gene (TaUGT-3B) single nucleotide polymorphism to identify resistant (T-allele) and susceptible (G-allele) markers. The progeny from the crosses were also screened for FHB severity using the immature spike culture method and identified resistant progeny grouped according to the HRM genotyping data. The results demonstrate a reliable approach using the immature spike culture to screen for FHB resistance in progeny of crosses in early stage of breeding programs.

• 한국약용작물학회지
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• 제25권5호
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• pp.290-295
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• 2017

Background: Senna tora is a flowering plant in the legume family Fabaceae. Its seeds are roasted and consumed as tea in Asia, to reduce inflammation in the liver and improve eyesight. Thus, it has been considered as an important medicinal crops in Asia. However, breeding trials to improve its genetic properties are rare. Mutation breeding by gamma ray is known to be an effective and highly successful approach for the generation of agronomically useful cultivars. Here we analyzed the effects of several dosages of gamma ray on the biological conditions of Senna tora seeds. Methods and Results: The germination rate and growth patterns of Senna tora were examined following irradiation with gamma ray at 100, 200, 300 and 400 Gy. The total phenolic compound contents and antioxidant activities of Senna tora were analyzed. Germination increased at 100 and 200 Gy in the M1 and M2 generations compared with that of the control (M0). The total phenolic compound contents and antioxidant activity of the seeds significantly decreased as the radiation dosage increased above 100 Gy in the M1 generation. Conclusions: Senna tora, irradiated with gamma ray at dosages 100, 200, 300, and 400 Gy, showed maximum germination rate at 200 Gy in the M2 generation. Plant height and leaf size gradually decreased with increasing gamma ray intensity in the M2 generation. The total phenolic compound contents decreased significantly at 400 Gy, and the related antioxidant activity was also decreased as the radiation dosage increased.

• 한국식품위생안전성학회:학술대회논문집
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• 한국식품위생안전성학회 1996년도 제11회 학술대회 및 정기총회 - 식품의 위생 안전성에 관한 최근 연구 동향
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• pp.33-33
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• 1996

Interests in the field of rapid methods and automation in microbiology have been growing steadily on an international scale in recent years. International meetings concerned this problem have been held in elsewhere in the world countries since the past twenty years. But, unfortunately in the field of microbial examination in food hygiene, this problem have not yet been developed so much as in the field of clinical microbiology. Today, I would like to introduce you here present aspects of rapid and automation technologies, those which are manly carrying in milk and meats industries. My illustration will be given recent improved technologies using automatic apparatus and instruments along with process of microbial count procedure. Recent direct microbiological counting system (ChemeScan \ulcorner) as real time ultrasensitive analysis created by Cheminex Ltd., France is now most evolutional instrument to provide direct microbial counts, down to one cell, within 30 minutes. The results from these evaluations how a good correlation between the ChemScan system and the standard plate count method. This system will be successful application for not only in the field of pharmacology but also food microbiology. In addition, current identification of microbes by sophisticated instruments suitable for food microbiology, one of which Biology is manual system (BIOLOG\ulcorner), provides reference-level capability at a modes price. For the manual system, the color reactions in the microplate are read by eye and manually keyed into personal computer. Species identification appears on the computer screen within seconds, along with biotype patterns, a list of closely related species, and other useful statistics. In present this is useful application for microbial ecology and epidemiological survey. RiboPrinter system newly produced by DuPont is now focusing among microbiologists in the world, and is one of the biggest microbial characterization system using a DNA-based approach. The technology analyzer is bacterial culture for its genetic fingerprint or riboprint pattern. Finally Bio-cellTracer system for automatic measurement of fungal growth and Fukitori-Maseter, a Surface Hygiene Monitoring Kit by using swabe procedure in food processing environment are briefly illustrated in this presentation.

• 한국지능시스템학회논문지
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• 제22권6호
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• pp.786-792
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• 2012

마이크로어레이는 수만 가지 이상의 DNA 또는 RNA를 기판위에 배열해 놓은 것이며 이 기술을 이용하여 대량의 유전자 발현을 탐색할 수 있게 되었다. 그렇지만 마이크로어레이는 실험자가 탐색하려는 특정 표현형에 대해서 설계된 실험방법을 이용하므로 제한된 숫자의 유전자 발현만을 관찰할 수 있다. 본 논문에서는 MicroRNAs(miRNAs)와 Protein-Protein Interaction(PPI) 정보를 포함하고 있는 데이터베이스를 활용하여 마이크로어레이 데이터의 의미적 확장 방법을 제시하고자 한다. 또한 Online Mendelian Inheritance in Man(OMIM) 및 International Statistical Classification of Diseases and Related Health Problems, $10^{th}$ Revision(ICD-10)을 이용하여 질병 간 유전적 공통점 파악을 시도하였다. 이러한 접근방법을 통하여 새로운 생물학적 시각을 제공할 수 있을 것으로 기대된다.

• 한국육종학회지
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• 제41권3호
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• pp.205-212
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• 2009

Wheat (Triticum aestivum L.) grain texture is an important determinant of milling properties and end product use. Two linked genes, puroindoline a (PINA) and puroindoline b (PINB), control most of the genetic variation in wheat grain texture. Wheat seed proteins were examined to identify PINA and PINB gene using two pre-harvest sprouting wheat cultivars; Jinpum (resistant) and Keumgang (susceptible).Wheat seed proteins were separated by two-dimensional electrophoresis with IEF gels over pH ranges: pH 3-10. A total of 73 spots were digested with trypsin resulting peptide fragmentation were analyzed by matrix assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF/MS). Mass spectra were automatically processed and searched through NCBInr, SWISS-PORT and MSDB database with mono isotopic masses and complete gene sequence were found by UniProt database. Puroindoline a and puroindoline b that is responsible for grain texture related with baking performance and roughness. Two spots were found Pin b (16.7 kDa) and Pin a (16.3 kDa) in Jinpum compare to seven spots were identified Pin a (16.1 kDa, 16.3 kDa) and Pin b (16.7 kDa, 9.5 kDa and 14.4 kDa) in Keumgang. Some selected spots were identified puroindoline like grain softness protein (16.9 kDa, 17 kDa and 18.1 kDa) in Keumgang. Moreover, to gain a better inferring the identification of puroindoline related proteins using proteomics, we accomplished a complete gene sequence of PINA and PINB gene in pre-harvesting sprouting wheat seeds between resistant (Jinpum) and susceptible (Keumgang).

• 전기전자학회논문지
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• 제23권2호
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• pp.529-533
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• 2019

오늘날 복합 화력 발전소는 전력 생산을 위해 많이 사용되고 있고, 최근에는 운전 매개 변수를 기반으로 발전 출력을 예측하는 것이 주요 관심사이다. 본 논문에서는 복합 화력 발전소의 출력을 예측하기 위해 컴퓨터 지능 기법을 이용하는 방법을 제시한다. 컴퓨터 지능 기술은 지속적으로 발전되어 많은 실제 문제에 적용되어 왔다. 본 논문에서는 트리 구조의 퍼지 뉴럴 네트워크를 이용하여 발전 출력을 예측하고자 한다. 트리 구조의 퍼지 뉴럴 네트워크는 퍼지 뉴런을 노드로 선택하고 관련 입력을 최적으로 선택하여 규칙 수를 줄이는 장점이 있다. 네트워크의 최적화를 위해 2 단계 최적화 방법이 사용된다. 유전 알고리즘은 최적의 노드와 리프를 선택하여 네트워크의 이진 구조를 최적화 한 다음 랜덤 신호 기반 학습을 수행하여 최적화 된 이진 연결을 단위 구간에서 미세 학습한다. 제안 된 방법의 유용성을 검증하기 위해 UCI Machine Learning Repository Database에서 얻은 복합 화력 발전소 데이터를 사용한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1260-1283
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• 2019

Low earth orbit (LEO) satellite broadband network is a crucial part of the space information network. LEO satellite constellation design is a top-level design, which plays a decisive role in the overall performance of the LEO satellite network. However, the existing works on constellation design mainly focus on the coverage criterion and rarely take network performance into the design process. In this article, we develop a unified framework for constellation optimization design in LEO satellite broadband networks. Several design criteria including network performance and coverage capability are combined into the design process. Firstly, the quality of service (QoS) metrics is presented to evaluate the performance of the LEO satellite broadband network. Also, we propose a network stability model for the rapid change of the satellite network topology. Besides, a mathematical model of constellation optimization design is formulated by considering the network cost-efficiency and stability. Then, an optimization algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is provided for the problem of constellation design. Finally, the proposed method is further evaluated through numerical simulations. Simulation results validate the proposed method and show that it is an efficient and effective approach for solving the problem of constellation design in LEO satellite broadband networks.

• Computers and Concrete
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• 제27권4호
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• pp.333-341
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• 2021

Steel slag, an industrial reject from the steel rolling process, has been identified as one of the suitable, environmentally friendly materials for concrete production. Given that the coarse aggregate portion represents about 70% of concrete constituents, other economic approaches have been found in the use of alternative materials such as steel slag in concrete. Unfortunately, a standard framework for its application is still lacking. Therefore, this study proposed functional model equations for the determination of strength properties (compression and splitting tensile) of steel slag aggregate concrete (SSAC), using gene expression programming (GEP). The study, in the experimental phase, utilized steel slag as a partial replacement of crushed rock, in steps 20%, 40%, 60%, 80%, and 100%, respectively. The predictor variables included in the analysis were cement, sand, granite, steel slag, water/cement ratio, and curing regime (age). For the model development, 60-75% of the dataset was used as the training set, while the remaining data was used for testing the model. Empirical results illustrate that steel aggregate could be used up to 100% replacement of conventional aggregate, while also yielding comparable results as the latter. The GEP-based functional relations were tested statistically. The minimum absolute percentage error (MAPE), and root mean square error (RMSE) for compressive strength are 6.9 and 1.4, and 12.52 and 0.91 for the train and test datasets, respectively. With the consistency of both the training and testing datasets, the model has shown a strong capacity to predict the strength properties of SSAC. The results showed that the proposed model equations are reliably suitable for estimating SSAC strength properties. The GEP-based formula is relatively simple and useful for pre-design applications.