一个酵母合成网络用于反向工程和建模方法的体内评估
Irene Cantone1, Lucia Marucci, Francesco Iorio
1Telethon Institute of Genetics and Medicine, Naples 80131, Italy.
Cell
|March 31, 2009
概括
我们在酵母中创建了一个合成基因网络,以对系统生物学工具进行基准测试. 这种合成网络准确地预测了行为,并允许准确地重建基因相互作用.
科学领域:
- 分子生物学分子生物学
- 系统生物学 系统生物学
- 合成生物学 合成生物学
背景情况:
- 系统生物学模型基因调节网络从数据,而合成生物学构建它们 de novo.
- 目前评估建模和逆向工程方法的方法缺乏严格的比较.
- 合成生物学为这些计算工具的体内基准测试提供了一个平台.
研究的目的:
- 在酵母中构建和测试合成基因网络,IRMA,以对逆向工程和建模技术进行基准测试.
- 严格比较使用体内实验数据的不同计算方法的预测能力.
主要方法:
- 在Saccharomyces cerevisiae中构建了一个合成的五基因调节网络 (IRMA).
- 确保内源基因的最小干扰和对小分子的响应.
- 在各种扰动下收集时间序列和稳定状态基因表达数据.
主要成果:
- 一个半定量模型成功捕获并预测了合成网络的行为.
- 反向工程技术,包括微分方程和贝叶斯网络,从实验数据中准确推断出监管相互作用.
结论:
- 合成IRMA网络为系统生物学工具的体内验证提供了一个有价值的平台.
- 计算模型和反向工程方法在与合成系统进行基准比较时显示出显著的预测和推断能力.
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