Filtering and inference for stochastic oscillators with distributed delays.
Filtering and inference for stochastic oscillators with distributed delays.
复制标题
对具有分布式延迟的随机振荡器进行过滤和推断。
DOI：
10.1093/bioinformatics/bty782
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发表时间：
2019-04-15
期刊：
影响因子：
--
通讯作者：
Finkenstädt B
中科院分区：
文献类型：
--
作者：
Calderazzo S;Brancaccio M;Finkenstädt B
生物化学反应网络中分子物种的时间演化往往是由涉及多个物种和反应事件的复杂随机过程引起的。这种系统的推论受到实验数据相对稀疏的深刻挑战，因为测量通常限于在离散时间点测量的参与物种的一小部分。通过引入概率时间延迟，可以现实地实现对由负的翻译和转录反馈回路引起的振荡动力学的模型简化的需要。虽然这种方法产生了一个简化的模型，推理是具有挑战性的，并受到正在进行的研究。线性噪声近似（LNA）最近被提出来解决这种系统的随机形式，并将在这里利用。我们开发了一种新的滤波方法的LNA在随机系统中的分布延迟，它允许的参数值和不可观测的状态的随机负反馈模型推断从单变量的时间序列数据。模拟数据的方法的性能进行了测试。当该模型拟合到Cry1的成像数据时，获得了真实的数据的结果，Cry1是参与哺乳动物中枢生物钟的关键基因，通过小鼠视交叉上核中的荧光素酶报告基因构建体观察到。程序编写在MATLAB和统计软件Release 2016 B中，MathWorks，Inc.，美国马萨诸塞州纳蒂克。示例代码和Cry1数据可在GitHub https://github.com/scalderazzo/FLNADD上获得。 补充数据可在Bioinformatics在线获得。
The time evolution of molecular species involved in biochemical reaction networks often arises from complex stochastic processes involving many species and reaction events. Inference for such systems is profoundly challenged by the relative sparseness of experimental data, as measurements are often limited to a small subset of the participating species measured at discrete time points. The need for model reduction can be realistically achieved for oscillatory dynamics resulting from negative translational and transcriptional feedback loops by the introduction of probabilistic time-delays. Although this approach yields a simplified model, inference is challenging and subject to ongoing research. The linear noise approximation (LNA) has recently been proposed to address such systems in stochastic form and will be exploited here. We develop a novel filtering approach for the LNA in stochastic systems with distributed delays, which allows the parameter values and unobserved states of a stochastic negative feedback model to be inferred from univariate time-series data. The performance of the methods is tested for simulated data. Results are obtained for real data when the model is fitted to imaging data on Cry1, a key gene involved in the mammalian central circadian clock, observed via a luciferase reporter construct in a mouse suprachiasmatic nucleus. Programmes are written in MATLAB and Statistics Toolbox Release 2016 b, The MathWorks, Inc., Natick, Massachusetts, USA. Sample code and Cry1 data are available on GitHub https://github.com/scalderazzo/FLNADD. Supplementary data are available at Bioinformatics online.
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