Information flow in cellular systems

Information Theory has been applied to biological systems since the 20th century, but is just in the last decade when it irrupted again in cell biology. New experimental and theoretical advances have permitted the estimation of key variables necessary to measure the information flow in cellular networks. The concept of Shannon's entropy can be now extended for the analysis of communication channels in cells. Cellular communication channels have a different structure than the ones used in the field of communication technology, and their Shannon entropy is measured either from an adaptation of the original equation or by a new wider formulation. It has been shown that the combination of Information Theory with the frequency response analysis of dynamical systems allows the determination of the cell's genetic response to input signals with varying frequencies, amplitude and form, in order to determine if the cell can differentiate between various regimes of information flow from the environment.


The objective of this topic is to give an overview of nowadays state of art of the information and communication theory in animal and plant cells. The topic also covers the following research aspects: 1) structure and dynamics of genetic networks: 2) structure and dynamics of signaling systems; 3) experimental determination of the key parameters and variables necessary for measuring the flow of information in cellular systems; 4) effect of noise on the information flow in genetic and signaling networks; 5) coding and decoding of information in genetic networks.

However, these subjects are not exclusive and only represent the core of the themes that can be considered for publication.