An automaton analogue of unicellularity

DigiHive: Artificial Chemistry Environment for Modeling of Self-Organization Phenomena

The article presents the DigiHive system, an artificial chemistry simulation environment, and the results of preliminary simulation experiments leading toward building a self-replicating system resembling a living cell. The two-dimensional environment is populated by particles that can bond together and form complexes of particles. Some complexes can recognize and change the structures of surrounding complexes, where the functions they perform are encoded in their structure in the form of Prolog-like language expressions. After introducing the DigiHive environment, we present the results of simulations of two fundamental parts of a self-replicating system, the work of a universal constructor and a copying machine, and the growth and division of a cell-like wall. At the end of the article, the limitations and arising difficulties of modeling in the DigiHive environment are presented, along with a discussion of possible future experiments and applications of this type of modeling.

Experiments with a universe for molecular modelling of biological processes

A computer simulation program and results of preliminary simulations of an abstract two-dimensional universe are presented, in which biological and physical processes can be modelled at the molecular level. Two types of permanent elements (atoms) occupy squares of the universe: called 0 and 1. Atoms sharing a common square form a particle, with properties determined by its component atoms. Atoms, particles, and complexes of particles move and collide according to rules like those of classical mechanics. At a higher level of organization, the string of atoms in a particle is viewed as a program, whose execution can affect the space around the particle. The computer program (written in Turbo-Pascal language) can simulate the evolution of the universe starting from any given initial configuration of the particles. Three examples of simulations, showing the development of ordered spatial structures from initial sets of randomly distributed particles, illustrate the universe's potential in modelling various molecular processes.

A universe for molecular modeling of self-replication

An abstract two-dimensional universe is presented, in which self-replication can be modeled and studied by computer simulation. Two types of permanent elements (atoms) occupy squares of the universe. Atoms sharing a common square form a particle, with properties determined by its component atoms. Atoms, particles, and complexes of particles move and collide according to rules like those of classical mechanics. At a higher level of organization, the string of atoms in a particle is viewed as a program, whose execution can affect the space around the particle in ways similar to the operation of enzymes. Two systems that exhibit self-replication when embedded in the universe are demonstrated. The first is very simple showing elementary self-replication activity. The second is relatively elaborate and intended to show "on paper" how a collection of particle complexes could behave in a manner resembling mitosis in a simple cell.

Evolve II: a computer model of an evolving ecosystem

The Evolve II program is a model of an ecosystem in which organisms are allowed to evolve. Organisms are subject to a changeable environment and competition from other organisms for a limited food supply. The gene structure may change through mutation. A feature of Evolve II is that the magnitude of phenotypic change resulting from mutation is itself a property of the gene. The system was studied under a number of environmental variation schemes. We report three significant findings. Two species (lineages with distinctly different survival strategies) evolved and coexisted in the same environmental conditions. Organisms developed a resistance to phenotypic change in response to mutation in slowly varying environments. However, traits which favor survival of the individual at the expense of reproduction could in some cases undergo phenotypic change in response to mutation despite the fact that this did not favor the survival of the offspring. This demonstrates that gene structures can evolve which are advantageous from the standpoint of the lineage, but not advantageous from the standpoint of individual offspring.

Genome structure described by formal languages

Nucleic acid sequences may be looked upon as words over the alphabet of nucleotides. Naturally occurring DNAs and RNAs form subsets of the set of all possible words. The use of formal languages is proposed to describe the structure of these subsets. Regular languages defined by finite automata are introduced to demonstrate the application of the concept on RNA-phages of group I. This approach permits a concise characterization of grammatical patterns in genetic information.

Algorithmic specification as a technique for computing with informal biological models

Conceptual biological models can sometimes be usefully expressed in algorithmic form. Models expressed in this way are often capable of capturing more aspects of the complete system than could be captured by other modeling approaches, though in general each aspect is captured in a highly simplified way. Two examples are given. The first involves algorithmic specification of the theory of evolution. The second involves a recently implemented computational model of the brain. Work with such models has, to some extent, the style of experimental work. It often suggests interesting problems or exposes subtle features of the system whose importance has been overlooked.