Tsuruyama Tatsuaki
Clinical Research Center for Medical Equipment Development, Kyoto University Hospital, Shogoin-Kawahara-cho 54, Sakyo-ku, Kyoto 606-8057, Japan.
Department of Drug Discovery Medicine, Pathology Division, Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto 606-8315, Japan.
Entropy (Basel). 2018 Jun 5;20(6):438. doi: 10.3390/e20060438.
Kullback-Leibler divergence (KLD) is a type of extended mutual entropy, which is used as a measure of information gain when transferring from a prior distribution to a posterior distribution. In this study, KLD is applied to the thermodynamic analysis of cell signal transduction cascade and serves an alternative to mutual entropy. When KLD is minimized, the divergence is given by the ratio of the prior selection probability of the signaling molecule to the posterior selection probability. Moreover, the information gain during the entire channel is shown to be adequately described by average KLD production rate. Thus, this approach provides a framework for the quantitative analysis of signal transduction. Moreover, the proposed approach can identify an effective cascade for a signaling network.
库尔贝克-莱布勒散度（KLD）是一种扩展的互熵，当从先验分布转移到后验分布时，它被用作信息增益的度量。在本研究中，KLD应用于细胞信号转导级联的热力学分析，并作为互熵的替代方法。当KLD最小时，散度由信号分子的先验选择概率与后验选择概率的比值给出。此外，整个通道中的信息增益由平均KLD产生率充分描述。因此，这种方法为信号转导的定量分析提供了一个框架。此外，所提出的方法可以识别信号网络的有效级联。
