Aita Takuyo, Morinaga Shunichi, Husimi Yuzuru
Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan.
Bull Math Biol. 2004 Sep;66(5):1371-403. doi: 10.1016/j.bulm.2004.01.004.
A theory for describing evolution as adaptive walks by a finite population with M walkers (M > or = 1) on an anisotropic Mt. Fuji-type fitness landscape is presented, from a thermodynamical point of view. Introducing the 'free fitness' as the sum of a fitness term and an entropy term and 'evolutionary force' as the gradient of free fitness on a fitness coordinate, we demonstrate that the behavior of these theoretical walkers is almost consistent with the thermodynamical schemes. The major conclusions are as follows: (1) an adaptive walk (=evolution) is driven by an evolutionary force in the direction in which free fitness increases; (2) the expectation of the climbing rate obeys an equation analogous to the Einstein relation in Brownian motion; (3) the standard deviation of the climbing rate is a quantity analogous to the mean thermal energy of a particle, kT (x constant). In addition, on the interpretation that the walkers climb the landscape by absorbing 'fitness information' from the surroundings, we succeeded in quantifying the fitness information and formulating a macroscopic scheme from an informational point of view.
从热力学角度出发,提出了一种理论,用于描述有限种群(有(M)个行走者,(M\geq1))在各向异性富士山型适应度景观上作为适应性行走的进化过程。通过引入作为适应度项与熵项之和的“自由适应度”以及作为适应度坐标上自由适应度梯度的“进化力”,我们证明了这些理论行走者的行为几乎与热力学方案一致。主要结论如下:(1)适应性行走(即进化)由进化力朝着自由适应度增加的方向驱动;(2)攀爬速率的期望值遵循一个类似于布朗运动中爱因斯坦关系的方程;(3)攀爬速率的标准差是一个类似于粒子平均热能(kT)((x)为常数)的量。此外,基于行走者通过从周围环境吸收“适应度信息”来攀爬景观的解释,我们成功地对适应度信息进行了量化,并从信息角度制定了一个宏观方案。