Kobayashi Tetsuya J
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:2704-7. doi: 10.1109/EMBC.2013.6610098.
The cellular and intracellular dynamics are intrinsically stochastic and dynamic. However, whole biological system such as a cell or our body can function very robustly and stably even though they are composed of these stochastic reactions. To account for this riddling relation between macroscopic robustness and microscopic stochasticity, I propose a mechanism that information relevant for stable and reliable operation of a biological system is embedded in apparently stochastic and noisy behavior of their components. To show validity of this possibility, I demonstrates that information can actually be decoded from apparently noisy signal when it is processed by an appropriate dynamics derived by Bayes' rule. Next, I investigate biological relevance of this possibility by showing that several intracellular networks can implement this decoding dynamics. Finally, by focusing its dynamical properties, I show the mechanism how the derived dynamics can separate information and noise.
细胞和细胞内的动力学本质上是随机且动态的。然而，整个生物系统，如一个细胞或我们的身体，尽管由这些随机反应组成，却能非常稳健且稳定地发挥功能。为了解释宏观稳健性与微观随机性之间的这种令人费解的关系，我提出一种机制，即与生物系统稳定可靠运行相关的信息被嵌入其组成部分明显随机且有噪声的行为中。为了证明这种可能性的有效性，我证明当由贝叶斯法则推导的适当动力学对其进行处理时，信息实际上可以从明显有噪声的信号中解码出来。接下来，我通过展示几个细胞内网络可以实现这种解码动力学来研究这种可能性的生物学相关性。最后，通过关注其动力学特性，我展示了所推导的动力学如何分离信息和噪声的机制。
