CIF:SMALL:COLLABORATIVE: Soft-Logic Modeling and Design for Synthetic Biology

这个项目是一个多机构合作的项目，我们计划研究一种新的软逻辑方法来创建设计师基因？电路。基因电路是在实验室中使用基因组构建块制作的，并被用来控制工程细菌的特定行为。遗传电路的一个主要研究挑战是细胞中存在着高度的随机性--S的内部环境。信念网络为处理遗传系统中随机性的影响提供了一个定义明确的解决方案。我们建议研究如何应用信念网络来控制甚至利用随机性来实现新的和有用的遗传行为。我们的研究成果将用于改进一种名为iBioSim.的遗传设计软件应用程序。合成遗传电路有许多预期的好处，包括工业、环境和医疗应用。例如，理论上，细菌可以被改造成清理漏油、杀死肿瘤和运送药物，但前提是我们必须准确地控制细菌何时以及如何发挥作用。我们的研究将阐明控制高度随机的细菌系统所涉及的独特挑战，并将为社区提供解决这些挑战的严谨理论和实用技术。

This project is a multi-institutional collaboration in which we plan to investigate a new soft-logic approach for creating ?designer gene? circuits. Genetic circuits are crafted in the laboratory using genomic building blocks, and are used to control specific behaviors in engineered bacteria. A major research challenge for genetic circuits is that there is a high level of randomness in the cell?s internal environment. Belief networks provide a well-defined solution for handling the effects of randomness in genetic systems. We propose to study how belief networks can be applied to control and even exploit randomness to achieve new and useful genetic behaviors. Our research results will be used to improve a software application for genetic design called iBioSim.There are many anticipated benefits for synthetic genetic circuits, including industrial, environmental, and medical applications. For example, bacteria can theoretically be engineered to clean oil spills, kill tumors, and deliver medicines, but only if we can precisely control when and how the bacteria perform their functions. Our investigation will illuminate the unique challenges involved in controlling highly random bacterial systems and will provide the community with rigorous theory and practicable techniques that resolve these challenges.