• 전자공학회논문지
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• 제51권10호
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• pp.118-127
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• 2014

DNA 데이터 저장(Data storage)은 DNA의 염기 서열에 대용량의 디지털 데이터를 저장하는 방법으로, 차세대 정보 저장 매개물로 인식되고 있다. 본 논문에서는 DNA 스테가노그라픽 기반으로 비부호 DNA 서열(Noncoding DNA sequence)에 정보를 저장하는 방법을 제안한다. 제안한 방법은 암호화된 데이터들을 정수 변화표에 의하여 데이터 염기 서열로 변환한 후, 시드 정보, 및 섹터 길이로 구성된 은닉 키에 의하여 비부호 염기 서열에 은닉한다. 따라서 단백질의 유전 기능이 유지되고, 원 DNA 서열없이 정보가 검출되며, 변이에 의하여 발생되는 오류가 검출된다. 기존 방법과의 비교 실험을 통하여 제안한 방법이 높은 bpn를 가지는 저장 효율을 가지며, 패리티 염기에 의하여 은닉된 정보의 오류 위치를 검출할 수 있음을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.838-841
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• 2005

DNA Chip is able to show DNA-Data that includes diseases of sample to User by using complementary characters of DNA. So this paper studied Neural Network algorithm for Image data processing of DNA-chip. DNA chip outputs image data of colors and intensities of lights when some sample DNA is putted on DNA-chip, and we can classify pattern of these image data on user pc environment through artificial neural network and some of image processing algorithms. Ultimate aim is developing of pattern classifying algorithm, simulating this algorithm and so getting information of one's diseases through applying this algorithm. Namely, this paper study artificial neural network algorithm for classifying pattern of image data that is obtained from DNA-chip. And, by using histogram, gradient edge, ANN and learning algorithm, we can analyze and classifying pattern of this DNA-chip image data. so we are able to monitor, and simulating this algorithm.

• Genomics & Informatics
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• 제9권2호
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• pp.89-91
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• 2011

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.

• 전기학회논문지
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• 제58권7호
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• pp.1424-1434
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• 2009

DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.53-62
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• 2006

DNA microarray data analysis is a new technology to investigate the expression levels of thousands of genes simultaneously. Since DNA microarray data structures are various and complicative, the data are generally stored in databases for approaching to and controlling the data effectively. But we have some difficulties to analyze and control the data when the data are stored in the several database management systems or that the data are stored to the file format. The existing analysis tools for DNA microarray data have many difficult problems by complicated instructions, and dependency on data types and operating system. In this paper, we design and implement network-based analysis tool for obtaining to useful information from DNA microarray data. When we use this tool, we can analyze effectively DNA microarray data without special knowledge and education for data types and analytical methods.

• Genomics & Informatics
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• 제9권3호
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• pp.134-135
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• 2011

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.196-202
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• 2021

DNA sequencing provides fundamental data in genomics, bioinformatics, biology and many other research areas. With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. Those large volumes of data also require a fast transmission, effective storage, superior functionality and provision of quick access to any record. Data storage costs have a considerable proportion of total cost in the formation and analysis of DNA sequences. In particular, there is a need of highly control of disk storage capacity of DNA sequences but the standard compression techniques unsuccessful to compress these sequences. Several specialized techniques were introduced for this purpose. Therefore, to overcome all these above challenges, lossless compression techniques have become necessary. In this paper, it is described a new DNA compression mechanism of pattern matching extended Compression algorithm that read the input sequence as segments and find the matching pattern and store it in a permanent or temporary table based on number of bases. The remaining unmatched sequence is been converted into the binary form and then it is been grouped into binary bits i.e. of seven bits and gain these bits are been converted into an ASCII form. Finally, the proposed algorithm dynamically calculates the compression ratio. Thus the results show that pattern matching extended Compression algorithm outperforms cutting-edge compressors and proves its efficiency in terms of compression ratio regardless of the file size of the data.

• 정보처리학회논문지D
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• 제17D권3호
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• pp.175-184
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• 2010

최근 DNA 칩의 등장으로 유전자 관련 실험과 연구가 매우 용이해졌으며 이를 활용한 다양한 실험 결과로 대량의 데이터가 제공되고 있다. DNA칩에 의해 제공된 데이터는 2차원 행렬로 표현되며 하나의 축은 유전자를 나타내고 다른 하나의 축은 샘플정보를 나타낸다. 이러한 데이터에 대하여 빠른 시간 안에 좋은 품질의 군집화를 수행함으로써 이후의 분석 단계인 분류화 작업의 정확도와 효율성을 높일 수 있다. 본 논문에서는 생태계 모방 알고리즘의 하나인 Particle Swarm Optimization 알고리즘을 사용하여 방대한 양의 DNA칩 데이터에 대한 효율적인 군집화 기법을 제안하였으며 실험을 통해서 PSO 기반의 군집화 알고리즘이 기존의 군집화 알고리즘들보다 수행속도 및 품질 면에서 우수한 성능을 가짐을 보였다.

• 식물분류학회지
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• 제50권4호
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• pp.403-412
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• 2020

Colonies of three independent gametophytes (one that is filamentous and two that are ribbon-like) without sporophytes occur in Gyeonggi-do, Gangwon-do, Gyeongsang-do, and Jeju-do, Korea. They have a moss-like appearance at first sight, with tiny plantlets and gemmae, and grow in cool, shaded, relatively deep dint places of large rocks, such as the small caves in high mountains, close to valleys. The gametophytes were identified based on morphological and molecular data by chloroplast DNA (cpDNA) sequence data (rbcL, rps4 gene and rps4-trnS intergenic spacer). Here, rbcL, rps4 gene and rps4-trnS intergenic spacer data of one independent gametophyte distributed in Korea have the same morphology, DNA sequence and monophyletic group as Crepidomanes intricatum from the eastern United States. They also share the same cpDNA data with Crepidomanes schmidtianum recently reported from Korea. The other independent gametophyte should be Hymenophyllum wrightii based on cpDNA data. The last one was presumed to be Pleurosoriopsis makinoi based on molecular data. The taxonomic status was confirmed to be the forma of Hymenophyllum wrightii through a revision of Hymenophyllum wrightii f. serratum based on molecular data.

• 대한화학회지
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• 제28권3호
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• pp.185-193
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• 1984

송아지 胸線 DNA의 nucleotide 당 spermine 0.016 분자의 비율로 結合되는 spermine 濃度에서 그 DNA와 ethidium과의 結合에 對한 Hill 係數는 1.7인 反面에 spermine이 存在하지 않는 條件에서는 그 Hill 係數가 0.38이었다. Spermine에 依한 DNA의 viscometric titration data, 260nm에서의 anomalous absorbance-temperature profile 및 粘性度-溫度 樣相과 더불어 이 data를 基礎로 하여 spermine 結合에 依하여 誘發되는 conformational transition의 allosteric propagation이 DNA의 凝縮된 構造로의 單分子的 collapse에 관여됨을 豫測할 수 있다.