生物实验方案建模与优化语言
A Language for Modeling And Optimizing Experimental Biological Protocols
摘要：
自动化在所有实验室活动中变得无处不在，导致精确定义和编纂的实验室协议。然而，实验室协议和数学模型之间的集成仍然缺乏。模型描述物理过程，而协议定义实验过程中执行的步骤：两者都不涵盖另一个领域，尽管它们都试图描述相同的现象。理想情况下，我们应该从模型和测试步骤的综合描述开始，同时分析模型参数，设备公差和数据收集的不确定性。为此，我们提出了一种语言来建模和优化实验生化协议，促进这样一个综合的描述，并可以与实验数据相结合。我们提供了一个概率语义，我们的语言的基础上贝叶斯解释，正式表征的不确定性，在数据收集，底层模型，和协议操作。在一组案例研究中，我们说明了如何得到的框架允许自动化分析和优化的实验协议，包括吉布森组装协议。
英文摘要：
Automation is becoming ubiquitous in all laboratory activities, leading towards precisely defined and codified laboratory protocols. However, the integration between laboratory protocols and mathematical models is still lacking. Models describe physical processes, while protocols define the steps carried out during an experiment: neither cover the domain of the other, although they both attempt to characterize the same phenomena. We should ideally start from an integrated description of both the model and the steps carried out to test it, to concurrently analyze uncertainties in model parameters, equipment tolerances, and data collection. To this end, we present a language to model and optimize experimental biochemical protocols that facilitates such an integrated description, and that can be combined with experimental data. We provide a probabilistic semantics for our language based on a Bayesian interpretation that formally characterizes the uncertainties in both the data collection, the underlying model, and the protocol operations. On a set of case studies we illustrate how the resulting framework allows for automated analysis and optimization of experimental protocols, including Gibson assembly protocols.
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