图 书 馆
参数估计的模型简化Model Reduction for Parameter Estimation |
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| 课程网址: | http://videolectures.net/pesb07_mjolsness_mrf/ |
| 主讲教师: | Eric Mjolsness |
| 开课单位: | 加利福尼亚大学 |
| 开课时间: | 2007-04-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Estimating parameters in biochemical network models is a central but often difficult problem. A general approach that may be worth developing further is first to seek simplified or "reduced" models with fewer dynamical degrees of freedom, estimate parameters for the reduced models, and then use that information to constrain the corresponding parameters in the full model. This approach can leverage appropriate human expertise and could in principle be applied recursively. The choice of variables to eliminate during model reduction could also be made by clustering or other machine learning methods. Some relevant model reductions already exist for quasi-equilibrium models of transcriptional regulation networks, which could provide a starting point for this strategy. |
| 关 键 词: | 生化网络; 简化模型; 机器学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-13：lxf |
| 阅读次数: | 53 |