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KMID : 0811720060100000323
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Korean Journal of Physiology & Pharmacology
2006 Volume.10 No. 0 p.323 ~ p.0
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A SYSTEMS BIOLOGY APPROACH FOR UNDERSTANDING DIFFERENTIATION OF STEM CELL TO NEURON
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Kim Min-Jung
Kim Bo-Kyung
Lee Seo-Eun
Kim Jin-Hyuk
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Abstract
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Complicated life phenomena such as cell differentiation and cancer are inevitably associated with changes of numerous
genes and interactions among them. Therefore, it is proper way to observe various genes’ activities and infer relationship
among them from systemic view for identifying mechanism of phenotype. Systems biology is based on development of high throughput technology, bioinformatics and systemic view on biological events. In this context, systems biology is considered to be relevant for searching a genetic network model to explain complex life phenomena, through synthesizing information mined from varied large datasets. In this study, we try to understand differentiation of stem cell to neuron with a systems biology approach. 10k mouse gene expression data were acquired by performing six cDNA microarray experiments and reverse sigmoid transformation analysis. Each experiment was repeated four times. Linear combination model and pseudo-inverse matrix calculation were applied to analysis of gene expression data for deducing connection strength between significantly expressed genes and whole genes. Consequently, a genetic network was represented as a direct graph with scaled edge. This genetic network was decomposed into sub-networks for detailed investigation of its biological function. Moreover, hierarchical structures of inner and inter sub-networks were identified for estimating influence of each gene on the genetic network. The genetic network reconstructed throughout this study may be used as probable model for understanding mechanism of differentiation of stem cell to neuron. In order to reach true genetic network underlying phenotype, this genetic network model should be repeatedly verified and modified by follow-up experiments. Furthermore, estimated genes that have high influence on genetic network can be primary candidate targets of follow-up experiments.
Source: Korean J Physiol Pharmacol.2006 Oct;10(Suppl II):237
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KEYWORD
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systems biology, microarray, genetic network, differentiation
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