Modeling and estimation of dynamic EGFR pathway by data assimilation approach using time series proteomic data.
Modeling and estimation of dynamic EGFR pathway by data assimilation approach using time series proteomic data.
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DOI：
10.11234/gi1990.17.2_226
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
S. Tasaki;Masao Nagasaki;M. Oyama;H. Hata;Kazuko Ueno;Ryo Yoshida;T. Higuchi;S. Sugano;S. Miyano
中科院分区：
文献类型：
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作者：
S. Tasaki;Masao Nagasaki;M. Oyama;H. Hata;Kazuko Ueno;Ryo Yoshida;T. Higuchi;S. Sugano;S. Miyano
Cell Illustrator是一个基于扩展混合函数Petri网（HFPNe）的建模工具。通过使用Cell Illustrator，我们成功地模拟了生物途径，例如，代谢途径、基因调控网络、microRNA调控网络、细胞信号传导网络和细胞-细胞相互作用。最近发展的串联质谱联用液相色谱（LC/MS/MS）技术使研究人员能够量化细胞内各种蛋白质的动态分布。通过使用LC/MS/MS获得的蛋白质组数据已经相当有用的动力学引入HFPNe模型。在这里，我们报告的时间序列蛋白质组数据的第一次介绍我们的HFPNe模型。我们利用文献中的生物学数据构建了表皮生长因子受体信号转导通路模型。然后，在数据同化（DA）框架中用一些手动调整确定动力学参数，以便拟合Blagoev等人（Nat.Biotechnol.，22：1139-1145，2004）。通过使用生物背景知识添加或删除一些调节环，进一步完善了该计算机模型。DA框架被用来从改进的模型中选择最合理的模型。通过使用蛋白质组学数据，我们通过使用Cell Illustrator与DA框架结合半自动地构建了一个良好调谐的EGFR HFPNe模型。
Cell Illustrator is a model building tool based on the Hybrid Functional Petri net with extension (HFPNe). By using Cell Illustrator, we have succeeded in modeling biological pathways, e.g., metabolic pathways, gene regulatory networks, microRNA regulatory networks, cell signaling networks, and cell-cell interactions. The recent development of tandem mass spectrometry coupled with liquid chromatography (LC/MS/MS) technology has enabled researchers to quantify the dynamic profile of a wide range of proteins within the cell. The proteomic data obtained by using LC/MS/MS has been considerably useful for introducing dynamics to the HFPNe model. Here, we report the first introduction of the time-series proteomic data to our HFPNe model. We constructed an epidermal growth factor receptor signal transduction pathway model (EFGR model) by using the biological data available in the literature. Then, the kinetic parameters were determined in the data assimilation (DA) framework with some manual tuning so as to fit the proteomic data published by Blagoev et al. (Nat. Biotechnol., 22:1139-1145, 2004). This in silico model was further refined by adding or removing some regulation loops using biological background knowledge. The DA framework was used to select the most plausible model from among the refined models. By using the proteomic data, we semi-automatically constructed a well-tuned EGFR HFPNe model by using the Cell Illustrator coupled with the DA framework.