Trends in Ecology & Evolution
Volume 17, Issue 11, 1 November 2002, Pages 528-532
Journal home page for Trends in Ecology & Evolution

Review
The biology of digital organisms

https://doi.org/10.1016/S0169-5347(02)02612-5Get rights and content

Abstract

Digital organisms are self-replicating computer programs that mutate and evolve. They can be thought of as a domesticated form of computer virus that lives in, and adapts to, a controlled environment. Digital organisms provide a unique opportunity with which to study evolutionary biology in a form of life that shares no ancestry with carbon-based life forms, and hence to distinguish general principles of evolution from historical accidents that are particular to biochemical life. In terms of the complexity of their evolutionary dynamics, digital organisms can be compared with biochemical viruses and bacteria. Recent studies of digital organisms have addressed long-term evolutionary adaptation and the growth of complexity in evolving systems, patterns of epistatic interactions in various genetic backgrounds, and quasi-species dynamics.

Section snippets

Long-term adaptation

One of the cornerstones of evolutionary biology is the influence of mutation and selection on organisms over long periods (of the order of thousands of generations or more), because darwinian theory predicts macroevolution and the emergence of novelty on that timescale. However, this is also one of the most difficult aspects to study, because of the long generation time of most model organisms. Macroevolutionary changes in biochemical organisms can only be studied through the history of

Epistatic interactions

Understanding epistatic interactions among mutations is key to many important questions in evolutionary biology. For example, the mutational deterministic hypothesis of the origin of sex requires that the effects of several deleterious mutations are reinforcing (synergistic) in their effects 18., 19., 20., as opposed to mitigating (antagonistic). Likewise, Muller's ratchet can operate at a significantly reduced speed in the presence of synergistic interactions, but can be accelerated by

Quasi-species dynamics

The relevance of quasi-species evolution [38] for the understanding of bacterial and viral dynamics has been debated for the past 20 years 39., 40.. In a nutshell, the quasi-species concept states that asexual organisms evolve as cohesive groups of closely related mutants, and that selection acts on these mutant clouds (quasi-species), rather than on the individual organisms. To observe quasi-species effects, the mutation rates must be relatively high, of the order of one mutation per genome

Digital life genetics

To a human eye, the genome of an evolved digital organism appears to be a random collection of computer instructions, assembled without any planning or organization. However, a detailed inspection reveals that these genomes are surprisingly well organized, and that they can often be subdivided into functionally distinct blocks, which deserve to be called genes. These genes can be discovered as follows: one systematically replaces each instruction of the genome, one at a time, with a special

Conclusions

Research on digital life forms has reached a level of sophistication at which questions of biological relevance can be both addressed and answered. The main focus of digital life research is a sort of comparative biology, which attempts to extricate those aspects of simple living systems that are germane to the type of chemistry used, from those that are not [46]. Additionally, digital life can help to refine mathematical theories and aid in developing and quickly testing new hypotheses about

Acknowledgements

We thank R.E. Lenski and C. Ofria for extensive discussions and encouragement. This work was supported by the National Science Foundation under contract No DEB-9981397. Part of this work was carried out at the Jet Propulsion Laboratory, under a contract with the National Aeronautics and Space Administration.

Glossary

Computational metabolism
the total set of computational reactions that an organism can do.
Computational reaction
a computation carried out by an organism on numbers provided by the environment. To achieve such a reaction, the organisms must possess a computational gene (code) or pathway for this reaction.
Explicit mutation
change in the genome between parent and offspring that is caused by noise in the environment (copy mutation, insertion mutation, deletion mutation, etc.)
Genome
the program

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