The complex biological processes, such as pericyte-to-neuron transition, pluripotency-to-hepatocyte transition, and epithelial-to-mesenchymal transition, involve pre-transition or critical states ...

Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in ...

The aim of this paper is to propose a general theoretical construction that allows us to associate a given class of complex systems with a suitable information measure adapted to this class, and ...

Entropy is also a measure of the uncertainty or ignorance of an observer observing the system’s macrostate and not knowing the specific microstate. Because states with higher disorder have more ...