• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.14-20
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• 2019

Currently, microarray gene expression data take advantage of the sufficient classification of cancers, which addresses the problems relating to cancer causes and treatment regimens. However, the sample size of gene expression data is often restricted, because the price of microarray technology on studies in humans is high. We propose enhancing the gene expression classification of support vector machines with generative adversarial networks (GAN-SVMs). A GAN that generates new data from original training datasets was implemented. The GAN was used in conjunction with nonlinear SVMs that efficiently classify gene expression data. Numerical test results on 20 low-sample-size and very high-dimensional microarray gene expression datasets from the Kent Ridge Biomedical and Array Expression repositories indicate that the model is more accurate than state-of-the-art classifying models.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보 워크샵 (DNA Chip Bioinformatics)
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• pp.117-150
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• 2001

cDNA Microarray 처리를 위한 시스템 개발에 관하여 개발시의 주요 착안점과 이전의 시스템에 비해서 개선된 몇 가지 기술에 대하여 본 연구팀의 실제적인 개발경험을 중심으로 설명한다. 렬 연구팀에서 만든 시스템의 기능은 이미지 처리부터 군집화(Clustering)에 이르는 전 과정을 통합적으로 처리될 수 있는데, 이 각 과정에 대하여 개략적으로 설명한다. 그리고 이 시스템을 활용하여 Macroarray라고 불릴 수 있는 새로운 형식의 array 실험장치에 어떻게 본 시스템이 적용되는지에 대하여도 설명을 한다.

• BMB Reports
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• 제39권3호
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• pp.247-252
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• 2006

A rapid method for the detection of Hepatitis E Virus (HEV) was developed by utilizing nano-gold labeled oligonucleotide probes, silver stain enhancement and the microarray technique. The 5'-end -$NH_2$ modified oligonucleotide probes were immobilized on the surface of the chip base as the capture probe. The detection probe was made of the 3'-end -SH modified oligonucleotide probe and nano-gold colloid. The optimal concentrations of these two probes were determined. To test the detection sensitivity and specificity of this technique, a conservative fragment of the virus RNA was amplified by the RT-PCR/PCR one step amplification. The cDNA was hybridized with the capture probes and the detection probes on microarray. The detection signal was amplified by silver stain enhancement and could be identified by naked eyes. 100 fM of amplicon could be detected out on the microarray. As the results, preparation of nano-gold was improved and faster. Development time also was shortened to 2 min. Thus, considering high efficiency, low cost, good specificity and high sensitivity, this technique is alternative for the detection of HEV.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2001년도 제2회 생물정보 워크샵 (DNA Chip Bioinformatics)
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• pp.29-44
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• 2001

DNA damage by physical insult including UV and g-radiation might provoke genetic alterations in cells, which is followed by either acute cell death or tumorigenesis. The responsiveness to g-radiation depends on cellular context of target cells. To understand the mechanisms of checkpoint control, repair and cell death following genotoxic stimu]i, cDNA microarray can provide the gene expression profile. To make a profile of gene expression in irradiated Jurkat T cells, we hybridized the cDNA microarray using cDNA from g-irradiated Jurkat T cells. Jurkat T cells were exposed to 4Gy to 16Gy, and total RNA were extracted at 4 to 24 hrs after irradiation. The hybridization of the microarray to fluorescence-labeled cDNA from treated and untreated cells was analyzed by bioinformatic analysis to address relative changes in expression levels of the genes present in the array. Responses varied widely in different time points, suggesting acute stress response and chronic restoration or cell death. From these results we could select 384 genes related to radiation response in Tcells, and radiation response might be different in various types of cells. Using Radchip, we could separate "the exposed" from control PBMCs. We propose that Radchip might be useful to check the radiation research as well as radiation carcinogenesis.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.107-116
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• 2004

The advent of microarray technologies gives an opportunity to moni tor the expression of ten thousands of genes, simultaneously. Such microarray data can be deteriorated by experimental errors and image artifacts, which generate non-negligible outliers that are estimated by 15% of typical microarray data. Thus, it is an important issue to detect and correct the se faulty probes prior to high-level data analysis such as classification or clustering. In this paper, we propose a systematic procedure for the detection of faulty probes and its proper correction in Genechip array based on multivariate statistical approaches. Principal component analysis (PCA), one of the most widely used multivariate statistical approaches, has been applied to construct a statistical correlation model with 20 pairs of probes for each gene. And, the faulty probes are identified by inspecting the squared prediction error (SPE) of each probe from the PCA model. Then, the outlying probes are reconstructed by the iterative optimization approach minimizing SPE. We used the public data presented from the gene chip project of human fibroblast cell. Through the application study, the proposed approach showed good performance for probe correction without removing faulty probes, which may be desirable in the viewpoint of the maximum use of data information.

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2005년도 The 14th Korea Genome Conference
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• pp.65-65
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• 2005

• Asian Pacific Journal of Cancer Prevention
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• 제17권5호
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• pp.2519-2525
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• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.51-56
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• 2005

There are many sources of systematic variations in cDNA microarray experiments which affect the measured gene expression levels like differences in labeling efficiency between the two fluorescent dyes. Print-tip lowess normalization is used in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. However, print-tip lowess normalization performs poorly in situation where error variability for each gene is heterogeneous over intensity ranges. We proposed the new print-tip normalization methods based on support vector machine regression(SVMR) and support vector machine quantile regression(SVMQR). SVMQR was derived by employing the basic principle of support vector machine (SVM) for the estimation of the linear and nonlinear quantile regressions. We applied our proposed methods to previous cDNA micro array data of apolipoprotein-AI-knockout (apoAI-KO) mice, diet-induced obese mice, and genistein-fed obese mice. From our statistical analysis, we found that the proposed methods perform better than the existing print-tip lowess normalization method.

• Molecules and Cells
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• 제24권1호
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• pp.105-112
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• 2007

Most neuroblastoma cells have chromosomal aberrations such as gains, losses, amplifications and deletions of DNA. Conventional approaches like fluorescence in situ hybridization (FISH) or metaphase comparative genomic hybridization (CGH) can detect chromosomal aberrations, but their resolution is low. In this study we used array-based comparative genomic hybridization to identify the chromosomal aberrations in human neuroblastoma SH-SY5Y cells. The DNA microarray consisting of 4000 bacterial artificial chromosome (BAC) clones was able to detect chromosomal regions with aberrations. The SH-SY5Y cells showed chromosomal gains in 1q12~ q44 (Chr1:142188905-246084832), 7 (over the whole chro-mosome), 2p25.3~p16.3 (Chr2:18179-47899074), and 17q 21.32~q25.3 (Chr17:42153031-78607159), while chromosomal losses detected were the distal deletion of 1p36.33 (Chr1:552910-563807), 14q21.1~q21.3 (Chr14:37666271-47282550), and 22q13.1~q13.2 (Chr22:36885764-4190 7123). Except for the gain in 17q21 and the loss in 1p36, the other regions of gain or loss in SH-SY5Y cells were newly identified.

• Asian-Australasian Journal of Animal Sciences
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• 제25권10호
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• pp.1481-1492
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• 2012

The interaction of the genes involved in intestinal development is the molecular basis of the regulatory mechanisms of intestinal development. The objective of this study was to identify the significant pathways and key genes that regulate intestinal development in Landrace piglets, and elucidate their rules of operation. The differential expression of genes related to intestinal development during suckling time was investigated using a porcine genome array. Time sequence profiles were analyzed for the differentially expressed genes to obtain significant expression profiles. Subsequently, the most significant profiles were assayed using Gene Ontology categories, pathway analysis, network analysis, and analysis of gene co-expression to unveil the main biological processes, the significant pathways, and the effective genes, respectively. In addition, quantitative real-time PCR was carried out to verify the reliability of the results of the analysis of the array. The results showed that more than 8000 differential expression transcripts were identified using microarray technology. Among the 30 significant obtained model profiles, profiles 66 and 13 were the most significant. Analysis of profiles 66 and 13 indicated that they were mainly involved in immunity, metabolism, and cell division or proliferation. Among the most effective genes in these two profiles, CN161469, which is similar to methylcrotonoyl-Coenzyme A carboxylase 2 (beta), and U89949.1, which encodes a folate binding protein, had a crucial influence on the co-expression network.