Modeling Dynamical Parallelism in Bio-systems

Abstract

Among the many events that occur in the life of biological organisms there are multitudes of specific chemical transformations that provide the cell with usable energy and molecules needed to form its structure and coordinate its activities. These biochemical reactions, as well as all other cellular processes, are governed by basic principles of chemistry and physics. A significant factor that determines whether or not reactions could take place is the entropy (it measures the randomness of the system). This measure depends on various factors. In an abstract framework, all these factors, which describe the way molecules interact, can be expressed by means of a computable multi-valued function that, depending on the current state of the system, establishes the possible ways of the evolution of the system. Inspired by these facts, we introduce and study several bio-mimetic computational rewriting systems that use discrete components (i.e., finite alphabets, finite set(s) of rewriting rules, etc.) and perform their computational steps in a non-deterministic manner and in a degree of rewriting parallelism that depends on the current state of the system, both specified by a given multi-valued function. Furthermore, we describe systems which produce the same output independently of the values taken by the considered functions.