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酵母中一种新型合成调控网络计算模型的推导、识别与验证。

Derivation, identification and validation of a computational model of a novel synthetic regulatory network in yeast.

作者信息

Marucci Lucia, Santini Stefania, di Bernardo Mario, di Bernardo Diego

机构信息

Telethon Institute of Genetics and Medicine (TIGEM), 80131 Naples, Italy.

出版信息

J Math Biol. 2011 May;62(5):685-706. doi: 10.1007/s00285-010-0350-z. Epub 2010 Jun 12.

Abstract

Systems biology aims at building computational models of biological pathways in order to study in silico their behaviour and to verify biological hypotheses. Modelling can become a new powerful method in molecular biology, if correctly used. Here we present step-by-step the derivation and identification of the dynamical model of a biological pathway using a novel synthetic network recently constructed in the yeast Saccharomyces cerevisiae for In-vivo Reverse-Engineering and Modelling Assessment. This network consists of five genes regulating each other transcription. Moreover, it includes one protein-protein interaction, and its genes can be switched on by addition of galactose to the medium. In order to describe the network dynamics, we adopted a deterministic modelling approach based on non-linear differential equations. We show how, through iteration between experiments and modelling, it is possible to derive a semi-quantitative prediction of network behaviour and to better understand the biology of the pathway of interest.

摘要

系统生物学旨在构建生物途径的计算模型,以便在计算机上研究其行为并验证生物学假设。如果使用得当,建模可以成为分子生物学中一种新的强大方法。在这里,我们逐步介绍了使用最近在酿酒酵母中构建的用于体内逆向工程和建模评估的新型合成网络推导和识别生物途径动力学模型的过程。该网络由五个相互调节转录的基因组成。此外,它还包括一种蛋白质-蛋白质相互作用,并且其基因可以通过向培养基中添加半乳糖来开启。为了描述网络动态,我们采用了基于非线性微分方程的确定性建模方法。我们展示了如何通过实验和建模之间的迭代,得出网络行为的半定量预测,并更好地理解感兴趣途径的生物学特性。

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