Chemogenomic analysis of neuronal differentiation with pathway changes in PC12 cells

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题名:	Chemogenomic analysis of neuronal differentiation with pathway changes in PC12 cells
作者:	樋口亞紺;Lin, Jack Yu-Shih;Wu, Chien Liang;Liao, Chia Nan;Higuchi, Akon;Ling, Qing-Dong
贡献者:	工學院化學工程與材料工程學系
日期:	2016-01-01
上传时间:	2026-04-21 14:44:38 (UTC+8)
出版者:	Royal Society of Chemistry
摘要:	摘要： The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database creates networks from interrelations between molecular biology and underlying chemical elements. This allows for analysis of biologic networks, genomic information, and higher-order functional information at a system level. Through high throughput experiments and system biology analysis, we investigated the genes and pathways associated with NGF induced neuronal differentiation. We performed microarray experiments and used the KEGG database, system biology analysis, and annotation of pathway functions to study NGF-induced differentiation in PC12 cells. We identified 2020 NGF-induced genes with altered expressions over time. Cross-matching with the KEGG database revealed 830 genes; among which, 395 altered genes were found to have a 2-fold increase in gene expression over a two-hour period. We then identified 191 associated biologic pathways in the KEGG database; the top 15 pathways showed correlation with neural differentiation. These included the neurotrophin pathways, mitogen-activated protein kinase (MAPK) pathways, genes associated with axonal guidance and the Wnt pathways. The activation of these pathways synchronized with nerve growth factor (NGF)-induced differentiation in PC12 cells. In summary, we have established a model system that allows one to systematically characterize the functional pathway changes in a group of neuronal population after an external stimulus. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database creates networks from interrelations between molecular biology and underlying chemical elements. 出版日期： 2015-12-15 識別號： ISSN: 1742-206X 識別號： EISSN: 1742-2051 識別號： DOI: 10.1039/c5mb00338e
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