• Interdisciplinary Bio Central
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• 제1권3호
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• pp.10.1-10.5
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• 2009

Toxicity is usually investigated using a set of standardized animal-based studies which, unfortunately, fail to detect all compounds that induce human adverse events and do not provide detailed mechanistic information of observed toxicity. As an alternative to conventional toxicology, toxicogenomics takes advantage of currently advanced technologies in genomics, proteomics, metabolomics, and bioinformatics to gain a molecular level understanding of toxicity and to enhance the predictive power of toxicity testing in drug development and risk/safety assessment. In addition, there has been a renewed interest, particularly in various government agencies, to prioritize and/or supplement animal testing with a battery of mechanistically informative in vitro assays. This article provides a brief summary of the issues, challenges and lessons learned in these fields and discuss the ways forward to further advance toxicology using these technologies.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.66-72
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• 2003

Toxicogenomics is now emerging as one of the most important genomics application because the toxicity test based on gene expression profiles is expected more precise and efficient than current histopathological approach in pre-clinical phase. One of the challenging points in Toxicogenomics is the construction of intelligent database management system which can deal with very heterogeneous and complex data from many different experimental and information sources. Here we present a new Toxicogenomics database developed as a part of 'Toxicogenomics for Efficient Safety Test (TEST) project'. The TEST database is especially focused on the connectivity of heterogeneous data and intelligent query system which enables users to get inspiration from the complex data sets. The database deals with four kinds of information; compound information, histopathological information, gene expression information, and annotation information. Currently, TEST database has Toxicogenomics information fer 12 molecules with 4 efficacy classes; anti cancer, antibiotic, hypotension, and gastric ulcer. Users can easily access all kinds of detailed information about there compounds and simultaneously, users can also check the confidence of retrieved information by browsing the quality of experimental data and toxicity grade of gene generated from our toxicology annotation system. Intelligent query system is designed for multiple comparisons of experimental data because the comparison of experimental data according to histopathological toxicity, compounds, efficacy, and individual variation is crucial to find common genetic characteristics .Our presented system can be a good information source for the study of toxicology mechanism in the genome-wide level and also can be utilized fur the design of toxicity test chip.

• 한국환경성돌연변이발암원학회:학술대회논문집
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• 한국환경성돌연변이발암원학회 2004년도 KSOT/KEMS Fall Annual Meeting
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• pp.135-135
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• 2004

• 유전체소식지
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• 제6권4호
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• pp.23-28
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• 2006

• Molecular & Cellular Toxicology
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• 제5권3호
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• pp.250-256
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• 2009

Toxicogenomics using microarray technology offers the ability to conduct large-scale detections and quantifications of mRNA transcripts, particularly those associated with alterations in mRNA stability or gene regulation. In this study, we developed the HazChem Human Array V2 using the Agilent Sure-Print technology-based custom array, which is expected to facilitate the identification of environmental toxicants. The array was manufactured using 600 VOCs and PAHs-specific genes identified in previous studies. In order to evaluate the viability of the manufactured HazChem human array V2, we analyzed the gene expression profiles of 9 environmental toxicants (6 VOCs chemicals and 3 PAHs chemicals). As a result, nine toxicants were separated into two chemical types-VOCs and PAHs. After the chip validations with VOCs and PAHs, we conducted an expression profiling comparison of additional chemical groups (POPs and EDCs) using data analysis methods such as hierarchical clustering, 1-way ANOVA, SAM, and PCA. We selected 58 genes that could be classified into four chemical types via statistical methods. Additionally, we selected 63 genes that evidenced significant alterations in expression with all 13 environmental toxicants. These results suggest that the HazChem Human Array V2 will expedite the development of a screening system for environmentally hazardous materials at the level of toxicogenomics in the future.

• 디지털콘텐츠학회 논문지
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• 제11권1호
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• pp.99-104
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• 2010

화학물질은 생체에 들어오면 여러 가지 독성반응을 나타내는데, 독성반응에 따른 유전자 발현을 분석하기 위해 바이오 칩 등을 이용한 신기술이 확산되면서 바이오 디지털 콘텐츠가 다량으로 생성되고 있다. 이 콘텐츠는 그 자체로는 의미가 적고 컴퓨터를 이용한 분석과 보정과정을 거쳐 생물학적으로 의미 있는 값들을 선별하여야 한다. 이런 콘텐츠에는 유전자들의 발현 양상 측정을 목적으로 하는 유전체학(genomics), 유전자의 발현 양상을 측정하는 전사체학(transcriptomics), 단백질의 발현을 측정하는 단백체학(proteomics), 대사체의 발현을 측정하는 대사체학(metabolomics) 등이 있으며, 이를 통칭하여 오믹스(omics)라고 부른다. 오믹스 기술을 독성을 연구하는 분야에 접목한 것이 독성유전체학(toxicogenomics)이며, 이에 대한 콘텐츠를 분석함으로써 독성을 예측하고 독성기전을 규명할 수 있다. 독성분석에 있어서 초기 단계의 분석은 향후 만성독성의 예측에 있어서 중요한 부분을 차지하고 있다. 바이오 디지털 콘텐츠를 이용하여 독성을 예측함에 있어 기존의 방법보다 더 빠르고 정확하게 예측하기 위해서는 많은 정보에 대한 분석기술의 진보가 필요하다. 또, 바이오 디지털 콘텐츠를 이용한 독성예측에 있어서 전체세포보다는 생물학적 현상을 일으키는 특이세포에서 이런 정보를 얻는 것이 중요하다고 생각된다. 또, 향후 바이오 디지털 콘텐츠 분석은 전략적 실험설계에 의한 데이터가 분석되고 축적되어야 하고, 분석알고리즘을 통한 네트워크 분석이 이루어져야 하며, 통합적 데이터 구축을 통해 이루어져야 할 것으로 생각된다.

• Molecular & Cellular Toxicology
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• 제1권2호
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• pp.92-98
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• 2005

DNA microarray analysis of gene expression in toxicogenomics typically requires relatively large amounts of total RNA. This limits the use of DNA microarray when the sample available is small. To confront this limitation, different methods of linear RNA amplification that generate antisense RNA (aRNA) have been optimized for microarray use. The target preparation strategy using amplified RNA in DNA microarray protocol can be divided into direct-incorporation labeling which resulted in cDNA targets (Cy-dye labeled cDNA from aRNA) and indirect-labeling which resulted in cRNA targets (i.e. Cy-dye labeled aRNA), respectively. However, despite the common use of amplified targets (cDNA or cRNA) from aRNAs, no systemic assessment for the use of amplified targets and bias in terms of hybridization performance has been reported. In this investigation, we have compared the hybridization performance of cRNA targets with cDNA targets from aRNA on a 10 K cDNA microarrays. Under optimized hybridization conditions, we found that 43% of outliers from cDNA technique and 86% from the outlier genes were reproducibly detected by both targets hybridization onto cDNA microarray. This suggests that the cRNA labeling method may have a reduced capacity for detecting the differential gene expression when compared to the cDNA target preparation. However, further validation of this discordant result should be pursued to determine which techniques possesses better accuracy in identifying truly differential genes.

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2006년도 The 15th Korean Genome Organization Conference KOGO 2006 Annual Meeting
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• pp.68-68
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• 2006

• 한국환경성돌연변이발암원학회:학술대회논문집
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• 한국환경성돌연변이발암원학회 2003년도 추계학술대회
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• pp.29-30
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• 2003

• 한국환경성돌연변이발암원학회:학술대회논문집
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• 한국환경성돌연변이발암원학회 2002년도 Molecular and Cellular Response to Toxic Substances
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• pp.116-116
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• 2002