• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.1197-1200
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• 2010

Post-genomic 시대에 접어들면서 단백질의 기능의 주석이 중요한 문제로 떠오르기 시작하였다. 이런 단백질 기능을 예측하기 위해 단백질 상호작용(Protein-Protein interaction) 데이터를 이용한 방법들이 지난 10여 년간 발표되어왔다. 단백질 상호작용(Protein-Protein interaction) 데이터는 단백질들 간의 서열 등의 특징을 이용해 상호간의 연결 관련성이 있는 단백질끼리의 관계를 네트워크로 나타낸 자료이다. 현재 이러한 단백질 상호작용(Protein-Protein interaction) 데이터들은 MIPS, DIP, BioGrid등 약 5~6군데에서 제공되고 있다. 각각의 데이터는 다른 형식을 가지고 있고, 중복되는 정보도 포함하고 있다. 여러 연구 방법에서 데이터를 사용할 때 한군데에서만 추출하기 보다는 여러 데이터에서 추출하는 경우가 많기 때문에 다른 형식의 데이터를 이용하는데 불필요한 수고가 들어가게 된다. 때문에 여러군데의 데이터를 한 가지 형식으로 맞추어 통합적으로 구축하여 연구 시 데이터 사용에 용이하도록 설계 하였다. 또한 발표된 단백질 기능 예측 방법에 대한 정리를 통해 앞으로의 연구를 하는데 있어서 필요한 자료를 얻고 열람할 수 있도록 설계하였다. 이를 통해 관련 연구를 하거나 관심이 있는 사람들의 데이터를 검색하는데 많은 도움이 될 것이다.

• Interdisciplinary Bio Central
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• v.4 no.3
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• pp.7.1-7.8
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• 2012

With the development of many methods of studying the brain, the field of neuroscience has generated large amounts of information obtained from various techniques: imaging techniques, electrophysiological techniques, techniques for analyzing brain connectivity, techniques for getting molecular information of the brain, etc. A plenty of neuroinformatics databases have been made for storing and sharing this useful information and those databases can be publicly accessed by researchers as needed. However, since there are too many neuroinformatics databases, it is difficult to find the appropriate database depending on the needs of researcher. Moreover, many researchers in neuroscience fields are unfamiliar with using neuroinformatics databases for their studies because data is too diverse for neuroscientists to handle this and there is little precedent for using neuroinformatics databases for their research. Therefore, in this article, we review databases in the field of neuroscience according to both their methods for obtaining data and their objectives to help researchers to use databases properly. We also introduce major neuroinformatics databases for each type of information. In addition, to show examples of novel uses of neuroinformatics databases, we represent several studies that combine neuroinformatics databases of different information types and discover new findings. Finally, we conclude our paper with the discussion of potential applications of neuroinformatics databases.

• Korean Journal of Plant Resources
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• v.23 no.3
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• pp.214-222
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• 2010

Many research results have indicated that many kinds of useful ingredients are rich in buckwheat, which have high nutritional values and medicinal properties, so, buckwheat has been cultivated around Asia and Europe. In this paper, genetic diversity of common and tartary buckwheat germplasms were studied based on morphological and molecular markers in order to provide useful information for conservation and utilization of buckwheat genetic resources. The length, width, thick, value and weight of the seed of the common and tartary buckwheat were measured and analyzed by the statistics methods. The result has shown that there are morphological variation both in common buckwheat and tartary buckwheat seeds collected from different regions. It also has shown that the morphological variation of tartary seeds was significantly correlated to geographical regions. The nuclear ribosomal internal transcribed spacers (ITS) of the tartary buckwheat collected from different countries were cloned, sequenced and statistically analyzed. The data showed that ITS sequences were informative to analyze the phylogeny of the tartary buckwheat and the data also showed that the genetic distances varied among different tartary buckwheat seeds collected from different countries.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.257-269
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• 2023

This paper presents a method for detecting faults in data obtained from the Automatic Identification System (AIS) of surface vessels. The data include latitude, longitude, Speed Over Ground (SOG), and Course Over Ground (COG). We derive two methods that utilize two models: a constant state model and a derivative augmented model. The constant state model incorporates noise variables to account for state changes, while the derivative augmented model employs explicit variables such as first or second derivatives, to model dynamic changes in state. Generally, the derivative augmented model detects faults more promptly than the constant state model, although it is vulnerable to potentially overlooking faults. The effectiveness of this method is validated using AIS data collected at a harbor. The results demonstrate that the proposed approach can automatically detect faults in AIS data, thus offering partial assistance for enhancing navigation safety.

• Genomics & Informatics
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• v.9 no.4
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• pp.181-188
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• 2011

In planning a model-based phylogenic study for highly related ethnic data, the SNP marker number is an important factor to determine for relationship inferences. Genotype frequency data, utilizing a sub sampling method, from 63 Pan Asian ethnic groups was used for determining the minimum SNP number required to establish such relationships. Bootstrap random sub-samplings were done from 5.6K PASNPi SNP data. DA distance was calculated and neighbour-joining trees were drawn with every re-sampling data set. Consensus trees were made with the same 100 sub-samples and bootstrap proportions were calculated. The tree consistency to the one obtained from the whole marker set, improved with increasing marker numbers. The bootstrap proportions became reliable when more than 7,000 SNPs were used at a time. Within highly related ethnic groups, the minimum SNPs number for a robust neighbor-joining tree inference was about 7,000 for a 95% bootstrap support.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.83-91
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• 2020

Environmental conditions are known to impact human health and behavior, emotions such as pleasure, anxiety, and depression, and reduce stress. Interior design that elevates emotional comfort and satisfaction can help improve mental health and well-being. This study is a systematic review that analyzed previous empirical studies that explored the effect of interior design elements on the user's emotional response which is quantitatively evaluated by bio-signal and qualitatively evaluated through self-reported questionnaire surveys. This paper aims to derive the attributes of interior design and biometric indicators that affect the user's positive emotion through the synthesis of previous studies and to confirm the feasibility of measuring bio-signals as an objective evaluation tool for architectural design and as a quantitative research method. As a result of the review, the biometric data from EEG, fMRI, ECG, EMG, GSR, and eye-tracking were used to measure the participants' emotional responses, which were manifested as positive or negative depending on certain attributes of interior design such as the form, color, lighting, material and furniture. The attributes of interior design related to the positive emotional response were the curved shape, high ceiling, openness of space, and subdued tone colors. Standard lighting conditions and wooden spaces were related to stress reduction in terms of comfort and relaxation. The free arrangement of furniture was related to the user's positive emotions. On the other hand, consistent experimental protocols could not be found, and although the sample sizes of the studies were small, the studies have demonstrated the feasibility of the emotional response measurement by using the biometric data. Therefore this method can be a useful objective tool in the measurement of human-centric data in architectural design, and to develop the evidence-based design to induce positive emotions and minimize stress.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.573-584
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• 2003

Recent massive data generation by genomics and proteomics requires bioinformatic tools to extract the biological meaning from the massive results. Here we introduce ROSPath, a database system to deal with information on reactive oxygen species (ROS)-mediated cell signaling pathways. It provides a structured repository for handling pathway related data and tools for querying, displaying, and analyzing pathways. ROSPath data model provides the extensibility for representing incomplete knowledge and the accessibility for linking the existing biochemical databases via the Internet. For flexibility and efficient retrieval, hierarchically structured data model is defined by using the object-oriented model. There are two major data types in ROSPath data model: ‘bio entity’ and ‘interaction’. Bio entity represents a single biochemical entity: a protein or protein state involved in ROS cell-signaling pathways. Interaction, characterized by a list of inputs and outputs, describes various types of relationship among bio entities. Typical interactions are protein state transitions, chemical reactions, and protein-protein interactions. A complex network can be constructed from ROSPath data model and thus provides a foundation for describing and analyzing various biochemical processes.

• The KIPS Transactions:PartA
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• v.11A no.1
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• pp.75-80
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• 2004

To interact database data with GRID system, implementation and installation of data manipulation module which manipulates database data and its index is required. Developing a search system searching data on web-based database, and integrating it with grid system, it is possible that searching data on web and use it directly on GRID system without independent data module. So, we can build easy and effective grid system, and the system could have more flexible architecture adapting data change. In this paper, we propose a searching system which interacting web-based database with GRID systems. We integrated the searching system with a bio god system which runs virtual screening jobs. As a result, UB Grid (Universal Bio Grid) is constructed. Developer could reduce time and effort required to integrate web data to GRID system, and user could use UB Grid system easily and effectively.