Can I read Information-thermodynamic characterization of stochastic Boolean networks on EtoBox?

Information-thermodynamic characterization of stochastic Boolean networks by Otsubo, Shun; Sagawa, Takahiro is a scholarly article available to read on EtoBox.

What is Information-thermodynamic characterization of stochastic Boolean networks about?

Recent progress in experimental techniques has enabled us to quantitatively study stochastic and flexible behavior of biological systems. For example, gene regulatory networks perform stochastic information processing and their functionalities have been extensively studied. In gene regulatory networks, there are specific subgraphs called network motifs that occur at frequencies much higher than those found in randomized networks. Further understanding of the designing principle of such networks is highly desirable. In a different context, information thermodynamics has been developed as a theoretical framework that generalizes non-equilibrium thermodynamics to stochastically fluctuating systems with information. Here we systematically characterize gene regulatory networks on the basis of information thermodynamics. We model three-node gene regulatory patterns by a stochastic Boolean model, which receive one or two input signals that carry external information. For the case of a single input, we found that all the three-node patterns are classified into four types by using information-thermodynamic quantities such as dissipation and mutual information, and reveal to which type each

Author

Otsubo, Shun; Sagawa, Takahiro

Published

2018

Language

EN