title: A trade-off relationship between energetic cost and entropic cost for in vitro evolution.
abstract: In this paper, we consider two complementary cost functions for the landscape exploring processes to obtain the global optimum sequence through in vitro evolution protocol: one is the entropic cost C(etp), which is based on the deviation from the uniformity of a mutant distribution in sequence space, and the other is the energetic cost C(eng), which is based on the total number of sequences to be generated and evaluated. Based on a prior knowledge about the structure of a given fitness landscapes, the conductor of the experiment can think up the efficient search algorithm (ESA), which requires the minimum number of points (=sequences) to be searched up to the global optimum. For five typical fitness landscapes, we considered their respective (putative) ESA, C(etp)(*) and C(eng)(*) based on the ESA. As a result, we found a trade-off relationship between C(etp)(*) and C(eng)(*) for every case, that is, C(eng)(*)+C(etp)(*) is approximately equal to the logarithm of the volume of the sequence space. C(etp)(*) and C(eng)(*) are interpreted in terms of the information-theoretic concepts.
authors.affiliation: Graduate School of Science and Engineering, Saitama University, Saitama 338-8570, Japan. taita@mail.saitama-u.ac.jp
authors.forename: Takuyo
authors.initials: T
authors.lastname: Aita
mesh_terms: D000465:Algorithms; D019020:Directed Molecular Evolution / Q000379:methods*; D004734:Energy Metabolism / Q000502:physiology*; D019277:Entropy; D056084:Genetic Fitness / Q000235:genetics*; D008957:Models, Genetic; D057386:Search Engine