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Bayesian information decoding by a cell

机译:单元的贝叶斯信息解码

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摘要

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.
机译:外部引入信号的信息处理是细胞中信号转导途径和遗传调控网络的基本任务。由于细胞内部和外部都存在内在和外在的噪声,因此这种途径必须对破坏信号中包含的信息的噪声具有鲁棒性。尽管已通过实验阐明了途径的分子细节,但我们仍然不知道哪种细胞内反应与对噪声的鲁棒信息处理有关。在本文中,我首先采用贝叶斯解码理论推导了最优的信息解码动态。然后,我证明可以通过自动磷酸化自动去磷酸化循环(aPadP循环)实现这种最佳解码动力学。从分叉的角度来看,aPadP循环的动力学性质也将被揭示。此外,我将研究包括aPadP循环在内的几种细胞间反应对信息解码的效率。

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