• 한국정보과학회논문지:소프트웨어및응용
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• 제35권6호
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• pp.347-356
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• 2008

마이크로어레이는 분자 생물학 실험에 있어 중요한 도구로 사용되고 있으며, 마이크로어레이 데이타 분석을 위한 다양한 계산학적 방법이 개발되어 왔다. 그러나, 기존 분석방법은 주어진 조건에 영향을 주는 개별 유전자를 추출하는 데 강한 방면, 유전자 간의 복합작용에 의한 영향을 분석하기 힘들다는 단점을 가지고 있다. 하이퍼망 모델은 생물학적인 네트워크 작용을 모방한 구조이며, 계산과정에서 요소간의 복합작용을 직접 고려하기 때문에 기존 방법에서 다루기 힘들었던 요소간 상호작용 분석이 가능하다는 장점을 가진다. 본 논문에서는 마이크로어레이 데이타를 기반으로 microRNA(miRNA) 프로파일 분석을 위한 하이퍼망 분류 기법을 소개한다. 하이퍼망 분류기는 miRNA 쌍을 기본 요소로 하여 진화 과정을 통해 miRNA 분류 데이타를 학습한다. 학습된 하이퍼망으로부터 유의하다.고 판단되는 miRNA 모듈을 쉽게 추출할 수 있으며, 사용자는 추출된 모듈의 유치미성을 직접 판단할 수 있다. 하이퍼망 분류기는 암 관련 miRNA 발현 데이타 분류 실험을 통해 91.46%의 정확도를 보임으로써 기존 기계학습 방법에 비해 뛰어난 성능을 보여주었으며, 하이퍼망 분석을 통해 생물학적으로 유의한 miRNA 모듈을 찾을 수 있음을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2617-2622
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• 2003

The pH neutralization process has long been taken as a representative benchmark problem of nonlinear chemical process control due to its nonlinearity and time-varying nature. For general nonlinear processes, it is difficult to control with a linear model-based control method so nonlinear controls must be considered. Among the numerous approaches suggested, the most rigorous approach is the dynamic optimization. However, as the size of the problem grows, the dynamic programming approach is suffered from the curse of dimensionality. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach was proposed by Bertsekas and Tsitsiklis (1996). The NDP approach is to utilize all the data collected to generate an approximation of optimal cost-to-go function which was used to find the optimal input movement in real time control. The approximation could be any type of function such as polynomials, neural networks and etc. In this study, an algorithm using NDP approach was applied to a pH neutralization process to investigate the feasibility of the NDP algorithm and to deepen the understanding of the basic characteristics of this algorithm. As the global approximator, the neural network which requires training and k-nearest neighbor method which requires querying instead of training are investigated. The global approximator requires optimal control strategy. If the optimal control strategy is not available, suboptimal control strategy can be used even though the laborious Bellman iterations are necessary. For pH neutralization process it is rather easy to devise an optimal control strategy. Thus, we used an optimal control strategy and did not perform the Bellman iteration. Also, the effects of constraints on control moves are studied. From the simulations, the NDP method outperforms the conventional PID control.

• 생물정신의학
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• 제12권2호
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• pp.165-172
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• 2005

Objectives:The purpose of this study is to 1) conduct a discrimination analysis of schizophrenia and bipolar affective disorder using MMPI profile through artificial neural network analysis and logistic regression analysis, 2) to make a comparison between advantages and disadvantages of the two methods, and 3) to demonstrate the usefulness of artificial neural network analysis of psychiatric data. Procedure:The MMPI profiles for 181 schizophrenia and bipolar affective disorder patients were selected. Of these profiles, 50 were randomly placed in the learning group and the remaining 131 were placed in the validation group. The artificial neural network was trained using the profiles of the learning group and the 131 profiles of the validation group were analyzed. A logistic regression analysis was then conducted in a similar manner. The results of the two analyses were compared and contrasted using sensitivity, specificity, ROC curves, and kappa index. Results:Logistic regression analysis and artificial neural network analysis both exhibited satisfactory discriminating ability at Kappa index of greater than 0.4. The comparison of the two methods revealed artificial neural network analysis is superior to logistic regression analysis in its discriminating capacity, displaying higher values of Kappa index, specificity, and AUC(Area Under the Curve) of ROC curve than those of logistic regression analysis. Conclusion:Artificial neural network analysis is a new tool whose frequency of use has been increasing for its superiority in nonlinear applications. However, it does possess insufficiencies such as difficulties in understanding the relationship between dependent and independent variables. Nevertheless, when used in conjunction with other analysis tools which supplement it, such as the logistic regression analysis, it may serve as a powerful tool for psychiatric data analysis.

• Journal of Animal Science and Technology
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• 제60권10호
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• pp.25.1-25.10
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• 2018

The central dogma of gene expression propounds that DNA is transcribed to mRNA and finally gets translated into protein. Only 2-3% of the genomic DNA is transcribed to protein-coding mRNA. Interestingly, only a further minuscule part of genomic DNA encodes for long non-coding RNAs (lncRNAs) which are characteristically more than 200 nucleotides long and can be transcribed from both protein-coding (e.g. H19 and TUG1) as well as non-coding DNA by RNA polymerase II. The lncRNAs do not have open reading frames (with some exceptions), 3`-untranslated regions (3'-UTRs) and necessarily these RNAs lack any translation-termination regions, however, these can be spliced, capped and polyadenylated as mRNA molecules. The flexibility of lncRNAs confers them specific 3D-conformations that eventually enable the lncRNAs to interact with proteins, DNA or other RNA molecules via base pairing or by forming networks. The lncRNAs play a major role in gene regulation, cell differentiation, cancer cell invasion and metastasis and chromatin remodeling. Deregulation of lncRNA is also responsible for numerous diseases in mammals. Various studies have revealed their significance as biomarkers for prognosis and diagnosis of cancer. The aim of this review is to overview the salient features, evolution, biogenesis and biological importance of these molecules in the mammalian system.

• Journal of Ecology and Environment
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• 제33권4호
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• pp.377-389
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• 2010

Understanding the factors relevant to endangerment and the patterns of habitat locations in relation to protected areas is critically important for the conservation of rare species. Although 64 plant species have recently been listed as endangered species in Korea, this information has, until now, not been available, making appropriate management and conservation strategies impossible to devise. Thus, we collected information on potentially threatening factors, as well as information on the locations in which these species were observed. The potentially threatening factors were classified into seven categories. National parks, provincial parks, ecosystem conservation areas, and wetland conservation areas were defined as protected conservation areas. Korean digital elevation model data, along with the maps of all protected areas were combined with the maps of endangered plant species, and analyzed via Geographic Information Systems (GIS). Excluding the category of "small population", endangered plant species in Korea were associated more frequently with extrinsic factors than intrinsic factors. Considering land surface only, all conservation areas in Korea totaled 4.9% of the land, far lower than International Union for Conservation of Nature and Natural Resources (IUCN)'s 10% coverage target. At the species level, 69% of the endangered plant species were detected in conservation areas, mostly in national parks. However, this result demonstrates that 31% of endangered species inhabit areas outside the conservation zones. Furthermore, at the habitat level, a large proportion of endangered species were found to reside in unprotected areas, revealing "gaps" in protected land. In the face of rapid environmental changes such as population increases, urbanization, and climate changes, converting these gap areas to endangered species' habitats, or at least including them in habitat networks, will help to perpetuate the existence of endangered species.

• Molecules and Cells
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• 제40권9호
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• pp.621-631
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• 2017

Vaccinia-related kinase 1 (VRK1) and VRK3 are members of the VRK family of serine/threonine kinases and are principally localized in the nucleus. Despite the crucial roles of VRK1/VRK3 in physiology and disease, the molecular and functional interactions of VRK1/VRK3 are poorly understood. Here, we identified over 200 unreported VRK1/VRK3-interacting candidate proteins by affinity purification and LC-MS/MS. The networks of VRK1 and VRK3 interactomes were found to be associated with important biological processes such as the cell cycle, DNA repair, chromatin assembly, and RNA processing. Interactions of interacting proteins with VRK1/VRK3 were confirmed by biochemical assays. We also found that phosphorylations of XRCC5 were regulated by both VRK1/VRK3, and that of CCNB1 was regulated by VRK3. In liver cancer cells and tissues, VRK1/VRK3 were highly upregulated and its depletion affected cell cycle progression in the different phases. VRK3 seemed to affect S phase progression and G2 or M phase entry and exit, whereas VRK1 affects G1/S transition in the liver cancer, which could be explained by different interacting candidate proteins. Thus, this study not only provides a resource for investigating the unidentified functions of VRK1/VRK3, but also an insight into the regulatory roles of VRK1/VRK3 in biological processes.

• 생태와환경
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• 제37권4호통권109호
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• pp.373-377
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• 2004

France에서는 국가적 차원에서 지난 1994년부터 수역관리청 (French Water Agencies : Seine, Rhone-Mediterranee-Corse, Artois-Picardie, Rhin-Meuse and Adour-Garonne)과 연합한 농공환경연구소(CEMAGREF)의 주도로 France 영토 (France본토 및 부속 도서에 해외 영토가 지구상에 걸쳐 존재함) 내에서 신뢰도를 가지고 간단히 이용할 수 있는 수질감시망 방법론으로 실용적인 규조류 지수 (Indice Biologique Diatomees)를 만들기로 하였다. 물론 이전인 1970년대부터 Seine강 수역관리청에서 규조류 지수를 이용하기 시작하였고, 1990년대부터 다른 5개 수역관리청에서도 도입한 바가 있다. 이 후 1995년에 최초의 지수를 공표하였고, 지속적이고 정기적인 자료원의 최신화와 보강을 거듭하여 1996년에 최초로 6대 수역관리청에서 적용하였으며 1998년에는 미비한 자료를 완결시키고 기존의 프로그램을 재검토하여 2000년 6월에 표준화된 3번째 판인 IBD가 만들어졌다. 이 방법론은 France의 표준화법인 AFNOR에 NF T90-354로 출간되어 범용화단계를 시작하였다.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 2002년도 추계국제학술대회
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• pp.156-156
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• 2002

The goal of this study is to develop a biomarker used in monitoring abnormal behaviors of Japanese medaka (Oryzias latipes) as a model organism caused by hazardous chemicals that are toxic and persistent in the ecosystem. A widely used insecticide, diazinon (O, O-diethyl O- (2-isopropyl-4-methyl-6-pyrimidinyl) phosphorothioate), is highly neurotoxic to fish, and it is also well known that it causes vertebral malformation and behavioral changes of fish at relatively low concentrations. The fish behaviors were observed on a real time basis using an image processing and automatic data acquisition system. The genes potentially involved in the abnormal behaviors were cloned using suppression subtractive hybridization (SSH) technique. The untreated individuals showed common behavioral characteristics. When the test fish was affected by diazinon at a concentration of 0.1 and 1 ppm, some specific patterns were observed in its behavioral activity and locomotive tracks. The typical patterns were enhanced surfacing activity, opercular movement, erratic movement, tremors and convulsions as reported previously. The number of genes up-regulated tty diazinon treatment were 97 which includes 27 of unknown genes. The number of down-regulated genes were 99 including 60 of unknown genes. These gene expression patterns will be analyzed by the artificial neural networks such as self organization map (SOM) and multilayer perceptron (MLP), revealing the role of genes responsible for the behaviors. These results may provide molecular biological and neurobehavioral bases of a biomonitoring system for diazinon using a model organism such as fish.

• 센서학회지
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• 제21권1호
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• pp.59-67
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• 2012

It was reported that the latest sensor technology allow an 65536 conductive polymer sensor array to be made with broad but overlapping selectivity to different families of chemicals emulating the characteristics found in biological olfaction. However, the supernumerary redundancy always accompanies great error and risk as well as an inordinate amount of computation time and local minima in signal processing, e.g. neural networks. In this paper, we propose a new method to reduce the number of sensor for analysis by reducing redundancy between sensors and by removing unstable sensors using the cosine similarity method and to decide on representative sensor using FCM(Fuzzy C-Means) algorithm. The representative sensors can be just used in analyzing. And, we introduce DWT(Discrete Wavelet Transform) for data compression in the time domain as preprocessing. Throughout experimental trials, we have done a comparative analysis between gas sensor data with and without reduced redundancy. The possibility and superiority of the proposed methods are confirmed through experiments.

• Applied Biological Chemistry
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• 제34권4호
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• pp.379-385
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• 1991

12품종의 쌀로 부터 분리 정제한 전분의 2.5% (w/v) 현탁액을 각각 $65^{\circ}C$에서 $95^{\circ}C$까지 $5^{\circ}C$ 간격으로 30분간 가열 조리한 후, 전분 입자들의 형태학적 변화를 주사현미경으로 관찰 하였다. 품종에 관계없이 쌀 전분 입자들은 온도가 증가함에 따라 점진적인 형태학적 변화를 보여주었다. 이들 형태학적 변화는 전분의 팽윤도, 용해도 및 아밀로그라프점성 특성등과 밀접한 연관성을 보였다. 전분 입자로 부터 가용성 물질이 용출되는 것과 팽윤된 전분 입자가 그 자체의 독특한 형태를 잃고 서로 망상구조로 연결되면서 이들 리올로지 특성들의 급격한 증가를 가져왔다. 초기 팽윤 단계에서 전분 입자들의 독특한 구조손실 시기는 각각의 호화온도에 영향을 받았다. 호화 온도 이상의 높은 온도에서 전분 입자들이 삼차원적 망상구조를 형성하는 정도는 아밀로오스 함량이 감소할 수록 망상구조가 더 세밀해지며, 증가하는 경향을 보였다.