Abstract：
Building on and extending existing definitions of robustness and evolvability, we propose and utilize new formal definitions, with matching measures, of robustness and evolvability of systems with genotypes and corresponding phenotypes. We explain and show how these measures are more general and more representative of the concepts they stand for, than the commonly used/referenced measures originally proposed by Wagner. Further, a versatile digital modeling approach (BNK) is proposed that is inspired by NK systems. However, unlike NK systems, BNK incorporates a genotype and a phenotype, in addition to fitness. We develop and apply an Evolutionary Algorithm to a BNK-modeled system to find different types of perfect oscillators. We then map the resulting oscillating systems to possible genetic circuit realizations. Continuing with the synthetic biology theme, we also investigate the effect of noise in DNA synthesis on the predicted functionality of a DNA-based biosensor (i.e., its robustness), and we carry out a theoretical assessment of the evolvability of different types of ribozymes, undergoing directed evolution.
摘要：
建立和扩展现有的鲁棒性和可进化性定义，我们提出并利用新的形式定义，有了匹配的措施，具有基因型和相应表型的系统的鲁棒性和可进化性。我们解释并展示了这些措施是如何更笼统，更能代表它们所代表的概念的，而不是瓦格纳最初提出的常用/参考措施。Further,受NK系统的启发，提出了一种通用的数字建模方法(BNK)。然而,与NK系统不同，BNK包含基因型和表型，除了健身。我们开发了一种进化算法，并将其应用于BNK建模的系统，以找到不同类型的完美振荡器。然后，我们将产生的振荡系统映射到可能的遗传电路实现。继续合成生物学主题，我们还研究了DNA合成中的噪声对基于DNA的生物传感器的预测功能的影响(即，其鲁棒性)，我们对不同类型核酶的可进化性进行了理论评估，正在进行定向进化。
