一个简单蛋白质折叠进化模型的渐近首中时
Asymptotic hitting time for a simple evolutionary model of protein folding
摘要：
我们考虑两个版本的一个简单的进化算法模型蛋白质折叠温度为零：（1+1）-EA的LeadingOnes问题。在这个示意性模型中，蛋白质的结构，这是编码为长度为n的位串，通过顺序接触结合的随机途径演变到其天然构象。我们研究了平均情况下两种不同突变下首中时的渐近行为：一种是翻转比特串中随机选择的唯一比特，另一种是伯努利翻转比特串中的每个比特以概率c/n独立翻转。对于每个算法，我们证明了一个大数定律，一个中心极限定理，并比较两个模型的性能。
英文摘要：
We consider two versions of a simple evolutionary algorithm model for protein folding at temperature zero: the (1+1)-EA on the LeadingOnes problem. In this schematic model, the structure of the protein, which is encoded as a bit-string of length n, is evolved to its native conformation through a stochastic pathway of sequential contact bindings. We study the asymptotic behavior of the hitting time, in the mean case scenario, under two different mutations: the one flip which flips a unique bit chosen uniformly at random in the bit-string, and the Bernoulli flip which flips each bit in the bit-string independently with probability c/n. For each algorithm we prove a law of large numbers, a central limit theorem and compare the performance of the two models.
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