• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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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• v.9 no.2
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.251-254
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• 2004

Web-Bioconductor System은 유전자 분석에 대한 통계적 모듈과 그래픽 환경을 제공하는 R언어와 DNA chip 데이터의 분석을 수행하는 Bioconductor 패키지를 이용하여 웹으로 DNA chip 데이터를 분석할 수 있도록 설계한 시스템이다. 본 시스템은 DNA chip 데이터의 분석을 위해 사용자 계정 모듈, 데이터 입력 모듈, 전 처리 모듈, 유전자 차등 발현 분석 모듈, 결과 출력 모듈로 구성되어 있으며, 분석된 결과물은 HTML, 이미지, XLS 파일 형태로 제공된다. 웹을 이용하여 DNA chip 분석을 수행함으로써 인터넷이 가능한 곳이면 시간과 장소의 구분이 없이 DNA chip 데이터 분석이 가능하며, 인터넷으로 DNA chip 데이터 분석 자료를 공유할 수 있음으로 연구자들의 상호 의견 교환을 바탕으로 효율적인 분석이 가능할 것이다. 또한 기존의 R언어와 Bioconductor가 전산 지식이 부족한 사람들에게는 접근하기 어려운 점을 웹 인터페이스로 간단하게 구현함으로써 DNA chip 데이터 분석에 있어 용이성과 효율성을 중대하고 있다.

• Genomics & Informatics
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• v.9 no.3
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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.

• KSBB Journal
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• v.16 no.6
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• pp.538-546
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• 2001

An integrated data analysis program for DNA chip containing normalization, FDM analysis, various kinds of clustering methods, PCA, and SVD was applied to analyze combined yeast cell cycle data. This paper includes both comparisons of some clustering algorithms such as K-means, SOM and furry c-means and their results. For further analysis, clustering results from the integrated analysis program was used for function assignments to each cluster and for motif analysis. These results show an integrated analysis view on DNA chip data.

• KSBB Journal
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• v.16 no.4
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• pp.381-388
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• 2001

A program for integrated gene expression profile analysis such as hierarchical clustering, K-means, fuzzy c-means, self-organizing map(SOM), principal component analysis(PCA), and singular value decomposition(SVD) was made for DNA chip data anlysis by using Matlab. It also contained the normalization method of gene expression input data. The integrated data anlysis program could be effectively used in DNA chip data analysis and help researchers to get more comprehensive analysis view on gene expression data of their own.

• The KIPS Transactions:PartD
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• v.17D no.3
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• pp.175-184
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• 2010

Experiments and research on genes have become very convenient by using DNA chips, which provide large amounts of data from various experiments. The data provided by the DNA chips could be represented as a two dimensional matrix, in which one axis represents genes and the other represents samples. By performing an efficient and good quality clustering on such data, the classification work which follows could be more efficient and accurate. In this paper, we use a bio-inspired algorithm called the Particle Swarm Optimization algorithm to propose an efficient clustering mechanism for large amounts of DNA chip data, and show through experimental results that the clustering technique using the PSO algorithm provides a faster yet good quality result compared with other existing clustering solutions.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.151-163
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• 2001

- Overview of Bioinformatics and vision of Samsung SDS on it - Overview of Bio Chip and its market - Product roadmap with "Expert system for DNA chip data " - "UniBIO "as an integrated package of DNA chip data analysis - Demo of UniBIO

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.3
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• pp.159-163
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• 2000

The genome sequencing project has generated and will contitute to generate enormous amounts of sequence data. Since the first complete genome sequence of bacterium Haemophilus in fluenzae was published in 1995, the complete genome sequences of 2 eukaryotic and about 22 prokaryotic organisms have detemined. Given this everincreasing amounts of sequence information, new strategies are necessary to efficiently pursue the phase of the geome project- the elucidation of gene expression patterns and gene product function on a whole genome scale. In order to assign functional information to the genome sequence, DNA chip technology was developed to efficienfly identify the differential expression pattern of indepondent biogical samples. DNA chip provides a new tool for genome expreesion analysis that may revolutionize revolutionize many aspects of human kife including mew surg discovery and human disease diagnostics.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.64-67
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• 2008

DNA Chip을 이용한 실험은 그 결과에 대하여 대용량의 정보를 쏟아내고 있다. 이러한 데이터를 분석하는 다양한 기법 중, 미리 정해진 클래스에 데이터를 해당하는 클래스로 분류하는 기법인 분류화를 수행하여 의도한 목표를 위한 규칙을 찾아내고자 한다. 본 논문에서는 이를 위해 DNA Chip과 같은 방대한 양의 정보 분석에 대하여 적합한 생태계 모방 알고리즘인 PSO Algorithm을 사용하여 분류 규칙을 발견하여 이를 데이터에 적용, 분류하는 연구를 기술하고 있다.