Bayesian information decoding by a cell

Abstract

Information processing of externally introduced signals is a basic task of signal transduction pathways and genetic regulatory networks in a cell. Because of the presence of intrinsic and extrinsic noise inside and outside of a cell, such a pathway has to be robust to noise that undermines information contained in the signals. Even though molecular details of the pathways have been clarified experimentally, we still do not know what kind of intracellular reactions are relevant to the robust information processing to noise. In this work, I firstly derive an optimal information decoding dynamics by employing the theory of Bayesian decoding. Then, I demonstrate that this optimal decoding kinetics can be implemented by an auto-phosphorlation auto-dephosphorlation cycle (aPadP cycle). Dynamical properties of the aPadP cycle will also be revealed from the bifurcation viewpoint. Moreover, I will investigate efficiency of information decoding by several intercellular reactions including the aPadP cycle.