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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
[Modeling of p53 signaling pathway based on S-system equations]
Shunhui Liu1, Changli Tao, Zhenyi Huang
1College of Life Sciences & Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou 510006, China.
Abstract:
p53, as a transcription factor, is an important tumor suppressor gene and plays the key role in the p53-dependent gene regulatory network. Therefore, it is important to understand its biological function at the level of the whole system. In this paper, based on KEGG database and related literatures in English and Chinese, the interaction mode and quantitative relationship of the related molecules involved in p53 signaling pathway were extracted. By using S-system equations and 'Simulink' toolbox of Matlab7.0, a dynamic model of p53 signaling pathway was developed, and the dynamic regulatory characteristics of p53 signaling pathway were analyzed on model simulation. The results were in accord with the literatures and could reflect quantitatively the complex regulatory relationship between the interacting molecules involved in p53 signaling pathway. In addition, model simulation helped us find and identify the key molecules in this signaling pathway. Thus, this model can be used as a basis for the follow-up study of the relationship by precise and quantitative assessment.
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