Qubic: Biological Information Technology Systems: Self-Perfecting Genetic Circuits

EIA-0130613，法国加州理工学院Arnold：BITS：生物信息技术系统-BITS：自我完善遗传电路我们建议开发高效、进化的设计策略来构建功能从头开始的遗传电路。我们将把分子进化的方法应用到复杂的遗传系统中，这些方法已经被证明在改良或改变性质的蛋白质工程中非常成功，这些遗传系统涉及多个阻遏因子、操纵子和启动子。我们相信，进化将被证明普遍适用于优化单个设备以及复杂的遗传电路，我们的目标将是展示如何最好地执行进化搜索，以便建立设备库并将它们组装成功能电路。我们预计，这项研究将建立一个从头开始的遗传电路设计的一般策略，并为生物系统中信息处理的自然算法和生物复杂性提供新的见解。这项研究强有力地结合了电路设计中经典方法的优势(表征门的器件物理，然后用众所周知的元件组成电路)和适应机制(突变和选择)，这是生物系统的标志。

EIA-0130613Arnold, FrancesCalifornia Institute of TechnologyBITS: Biological Information Technology Systems - BITS: Self-Perfecting Genetic CircuitsWe propose to develop efficient, evolutionary design strategies for constructing functional de novo geneticcircuits. We will apply methods of molecular evolution, which have proven highly successful forengineering proteins with improved or altered properties, to complex genetic systems involving multiplerepressors, operators, and promoters. We believe that evolution will prove to be generally applicable foroptimizing individual devices as well as complex genetic circuits, and our goal will be to demonstratehow evolutionary searches are best performed in order to build libraries of devices and assemble theminto functional circuits.We anticipate that this research will establish a general strategy for de novo genetic circuit designand provide new insight into the natural algorithms of information processing in biological systems andbiological complexity. This research exploits, in powerful combination, the strengths of classicalapproaches in electrical circuit design (characterizing the device physics of gates, then composingcircuits from well understood components) with adaptation mechanisms (mutation and selection)that arethe hallmark of biological systems.