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Directed Acyclic Graph-Based Technology Mapping of Genetic Circuit Models

机译:基于有向无环图的遗传电路模型技术映射

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摘要

As engineering foundations such as standards and abstraction begin to mature within synthetic biology, it is vital that genetic design automation (GDA) tools be developed to enable synthetic biologists to automatically select standardized DNA components from a library to meet the behavioral specification for a genetic circuit. To this end, we have developed a genetic technology mapping algorithm that builds on the directed acyclic graph (DAG) based mapping techniques originally used to select parts for digital electronic circuit designs and implemented it in our GDA tool, iBioSim. It is among the first genetic technology mapping algorithms to adapt techniques from electronic circuit design, in particular the use of a cost function to guide the search for an optimal solution, and perhaps that which makes the greatest use of standards for describing genetic function and structure to represent design specifications and component libraries. This paper demonstrates the use of our algorithm to map the specifications for three different genetic circuits against four randomly generated libraries of increasing size to evaluate its performance against both exhaustive search and greedy variants for finding optimal and near-optimal solutions.
机译:随着合成生物学中诸如标准和抽象等工程基础的逐渐成熟,至关重要的是,必须开发基因设计自动化(GDA)工具,以使合成生物学家能够从文库中自动选择标准化的DNA组分,以满足遗传电路的行为规范。 。为此,我们开发了一种遗传技术映射算法,该算法建立在基于有向无环图(DAG)的映射技术的基础上,该映射技术最初用于选择数字电子电路设计的零件,并在我们的GDA工具iBioSim中实现了该技术。它是最早将电子电路设计中的技术应用于遗传技术的制图算法之一,尤其是使用成本函数来指导寻找最佳解决方案的方法,也许是最大程度地利用描述遗传功能和结构的标准的算法代表设计规范和组件库。本文演示了如何使用我们的算法针对四个随机生成的,逐渐增加大小的库来映射三个不同遗传电路的规范,以针对穷举搜索和贪婪变体来评估其性能,以找到最佳和接近最佳的解决方案。

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