BACKGROUND The gap between genotype and phenotype is filled by complex biochemical systems most of which are poorly understood. Because these systems are complex, it is widely appreciated that quantitative understanding can only be achieved with the aid of mathematical models. However, formulating models and measuring or estimating their numerous rate constants and binding constants is daunting. Here we present a strategy for automating difficult aspects of the process. METHODS The strategy, based on a system design space methodology, is applied to a class of 16 designs for a synthetic gene oscillator that includes seven designs previously formulated on the basis of experimentally measured and estimated parameters. RESULTS Our strategy provides four important innovations by automating: (1) enumeration of the repertoire of qualitatively distinct phenotypes for a system; (2) generation of parameter values for any particular phenotype; (3) simultaneous realization of parameter values for several phenotypes to aid visualization of transitions from one phenotype to another, in critical cases from functional to dysfunctional; and (4) identification of ensembles of phenotypes whose expression can be phased to achieve a specific sequence of functions for rationally engineering synthetic constructs. Our strategy, applied to the 16 designs, reproduced previous results and identified two additional designs capable of sustained oscillations that were previously missed. CONCLUSIONS Starting with a system's relatively fixed aspects, its architectural features, our method enables automated analysis of nonlinear biochemical systems from a global perspective, without first specifying parameter values. The examples presented demonstrate the efficiency and power of this automated strategy.

中文翻译：

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通过自动枚举和对表型库的分析来阐明基因型-表型图。

背景技术基因型和表型之间的鸿沟被复杂的生化系统所填补，其中大多数对此知之甚少。由于这些系统很复杂，因此人们普遍认识到，只有借助数学模型才能实现定量理解。然而，建立模型并测量或估计它们的众多速率常数和结合常数是艰巨的。在这里，我们提出了一种使流程困难的方面自动化的策略。方法该策略基于系统设计空间方法，被应用于合成基因振荡器的一类16种设计，其中包括先前根据实验测量和估计的参数制定的七种设计。结果我们的策略通过自动化实现了四个重要的创新：（1）列举系统中质上不同的表型库；（2）为任何特定表型生成参数值；（3）同时实现几种表型的参数值，以帮助可视化从功能表型到功能障碍的关键情况下从一种表型到另一种表型的转变；（4）鉴定表型的集合体，其表达可以被阶段化以实现合理地工程化合成构建体的特定功能序列。我们的策略应用于16个设计，重现了先前的结果，并确定了另外两个能够持续振荡的设计，而这些设计以前曾被遗漏。结论从系统的相对固定的方面，其体系结构特征，我们的方法无需全局指定参数值即可从全局角度自动分析非线性生化系统。所提供的示例演示了此自动化策略的效率和功能。