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(사)한국바이오칩학회 The Korean BioChip Society





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학술지 열람

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Info. Vol.6 - No.3 (2012.09.20)
Title The comparative analysis ofin vivoand in vitrotranscriptome data based on systems biology
Authors Yunju Jo1, Jung-Hwa Oh2, Seokjoo Yoon2, Hyunsu Bae1, Moo-Chang Hong1, Min-Kyu Shin1& YangSeok Kim1
Institutions 1Department of Physiology, College of Oriental Medicine, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul 130-701, Korea
2Division of Toxicological Research, Korea Institute of Toxicology, 141 Gajeong-ro Yuseong-gu, Daejeon 305-343, Korea
Correspondence and requests for materials should be addressed to Y.S. Kim(yskim1158@khu.ac.kr)
Abstract We investigated whether an in vitro cell based system can represent toxicity of anin vivo organ using gene expression profiles. We performed an analysis of differentially expressed transcripts, pathway analysis, and Gene Ontology(GO) grouping with the toxicity-induced data following treatments with diclofenac, sulindac, itraconazole, and ketoconazole. The number of genes regulatedin vitro andin vivowere much more than the randomly sampled number, but no significant correlation was observed between the in vitroand in vivo experiments. We performed a pathway analysis and GO grouping to expand the approach. In the pathway analysis, we narrowed down the hepatotoxic pathways to focus on toxicity. Then, the percentages of overlapping pathways increased. We found pathways associated with liver function in all experiments, such as the adipocyte signaling pathway, JAK-STAT signaling pathway, and peroxisome proliferator-activated receptor(PPAR) signaling pathway. In the GO grouping analysis, the clusters obtained were primarily related to lipid metabolic and synthetic processes. The percentage of common GO terms between in vitroandin vivoexperiments also increased. Therefore, we identified than an analysis performed at the systems biology level was more correlated for in vitro and in vivo systems.
Keyword Comparative analysis, Transcriptome data, In vitroandin vivo, Bioinformatics, Systems biology
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