首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >Moment-Based Parameter Estimation for Stochastic Reaction Networks in Equilibrium
【24h】

Moment-Based Parameter Estimation for Stochastic Reaction Networks in Equilibrium

机译:平衡条件下随机反应网络基于矩的参数估计

获取原文
获取原文并翻译 | 示例

摘要

Calibrating parameters is a crucial problem within quantitative modeling approaches to reaction networks. Existing methods for stochastic models rely either on statistical sampling or can only be applied to small systems. Here, we present an inference procedure for stochastic models in equilibrium that is based on a moment matching scheme with optimal weighting and that can be used with high-throughput data like the one collected by flow cytometry. Our method does not require an approximation of the underlying equilibrium probability distribution and, if reaction rate constants have to be learned, the optimal values can be computed by solving a linear system of equations. We discuss important practical issues such as the selection of the moments and evaluate the effectiveness of the proposed approach on three case studies.
机译:校准参数是反应网络定量建模方法中的关键问题。现有的随机模型方法要么依靠统计抽样,要么只能应用于小型系统。在这里,我们为平衡中的随机模型提供了一种推理程序,该程序基于具有最佳权重的矩匹配方案,并且可以与高通量数据(如通过流式细胞仪收集的数据)一起使用。我们的方法不需要近似的基本平衡概率分布,并且,如果必须学习反应速率常数,则可以通过求解线性方程组来计算最佳值。我们讨论了重要的实际问题,例如矩的选择,并在三个案例研究中评估了所提出方法的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号