Fariba Karimi

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53–mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to ‘pools of reversibility’. These natural subsystems are related to one another in a hierarchical manner by the notion of ‘weak control’. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Fuzzy Splicing Systems

In this paper we introduce a new variant of splicing systems, called fuzzy splicing systems, and establish some basic properties of language families generated by this type of splicing systems. We study the “fuzzy effect” on splicing operations, and show that the “fuzzification” of splicing systems can increase and decrease the computational power of splicing systems with finite components with respect to fuzzy operations and cut-points chosen for threshold languages.

THE CHARACTERIZATIONS OF DIFFERENT SPLICING SYSTEMS

The concept of splicing system was first introduced by Head in 1987 to model the biological process of DNA recombination mathematically. This model was made on the basis of formal language theory which is a branch of applied discrete mathematics and theoretical computer science. In fact, splicing system treats DNA molecule and the recombinant behavior by restriction enzymes and ligases in the form of words and splicing rules respectively. The notion of splicing systems was taken into account from different points of view by many mathematicians. Several modified definitions have been introduced by many researchers. In this paper, some properties of different kinds of splicing systems are presented and their relationships are investigated. Furthermore, these results are illustrated by some examples.

Crossing-Preserved and Persistent Splicing Systems

By the introduction of the notion of splicing system by Head in 1987, a new approach for bio-inspired problems was made. This mathematical model helps to interpret the behavior of restriction enzymes on DNA molecules when they are cut and pasted. The theoretical skeleton of this model was based on formal language theory. Several types of splicing systems have been defined by different mathematicians. One of those is the persistent splicing system in which the property of being crossing of a site is preserved. In this paper, we introduced two new concepts, namely self-closed and crossing-preserved splicing patterns. The connection of these concepts with the persistent splicing systems is investigated. Some examples are provided to illustrate the relations.