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细胞信号传导途径的数学模型
Mathematical Modeling of Cell Signalling Pathways |
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| 课程网址: |
http://videolectures.net/pim07_vera_mmc/
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| 主讲教师: |
Julio Vera González
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| 开课单位: |
罗斯托克大学
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| 开课时间: |
2007-11-06
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| 课程语种: |
英语
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| 中文简介: |
近年来，通过常微分方程（ODE）或其他范式（如随机模型）中的基于数据的模型对细胞信号系统进行分析，已成为理解细胞信号转导中发生的蛋白质相互作用的潜在复杂性的宝贵工具。与其他生物化学系统相比，细胞信号系统的建模面临着额外的困难，这与量化蛋白质-蛋白质过程的挑战有关，也与缺乏关于所考虑的网络相互作用的拓扑结构的完整信息有关。由于在大多数代谢系统中，完整的相互作用网络（实际上）是完美建立的，因此在细胞信号系统中，通路的真实结构是一个悬而未决的问题，需要并行或通过基于数学模型的分析来阐明。在这次演讲中，我们讨论了幂律模型在生物化学系统中的应用（优势和挑战）。我们还展示了如何通过数学建模将现有的生物学知识和定量数据整合起来，以验证关于信号通路结构的假设。
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| 课程简介: |
In recent years, the analysis of cell signalling systems through data-based models in ordinary differential equations (ODE) or other paradigms (e.g. stochastic models) has emerged as an invaluable tool to understand the underlying complexity of the protein interactions happening in cellular signal transduction. Compared with other biochemical systems, the modelling of cell signalling systems faces additional difficulties related to the challenges quantifying protein-protein processes but also to the lack of complete information about the topology of the considered network interactions. Since in most of the metabolic systems the complete network of interactions is (virtually) perfectly established, in cell signalling systems the real structure of the pathways is an open question to be elucidated either in parallel or through mathematical modelling based analysis. In this talk we discuss the use of power-law models (advantages and challenges) in biochemical systems. We also show how pre-existent biological knowledge and quantitative data can be integrated through mathematical modelling to validate hypothesis about the structure of signalling pathways.
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| 关 键 词: |
常微分方程; 细胞信号; 生物信息学
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| 课程来源: |
视频讲座网
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| 数据采集: |
2023-04-20：chenjy
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| 最后编审: |
2023-05-13：chenjy
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| 阅读次数: |
41
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