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扩展并应用Spartan进行时间敏感性分析,以预测计算模型中有影响力的生物途径的变化。

Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

作者信息

Alden Kieran, Timmis Jon, Andrews Paul S, Veiga-Fernandes Henrique, Coles Mark

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2017 Mar-Apr;14(2):431-442. doi: 10.1109/TCBB.2016.2527654. Epub 2016 Feb 11.

Abstract

Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

摘要

通过整合实时成像、计算建模和统计分析方法,先前的研究表明,与之前认为该过程由趋化因子介导的细胞募集触发的观点相反,细胞粘附因子的诱导和反应是早期淋巴组织发育中的关键起始途径。这些从模型得出的假设是使用Spartan开发的,Spartan是一个开源敏感性分析工具包,旨在建立并理解计算模型与该模型所捕捉的生物系统之间的关系。在此,我们扩展了Spartan的可用功能,以允许进行统计分析,对比计算模型在不同模拟时间点表现出的行为,从而进行时间分析,这可能表明生物机制的影响是否随时间变化。我们以淋巴组织发育的计算模型作为延时工具来举例说明这种扩展功能。通过以十二小时的间隔生成结果,我们展示了如何利用对Spartan的扩展来表明淋巴组织发育可能是双相的,并预测生物机制影响可能发生转变的时间点。

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