ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2017
Non-adaptive origins of evolutionary innovations increase network complexity in interacting digital organisms.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Ontology for the Avida digital evolution platform.Scientific data · 2023Article
- avidaR: an R library to perform complex queries on an ontology-based database of digital organisms.PeerJ. Computer science · 2023Article
- Plausible pathway for a host-parasite molecular replication network to increase its complexity through Darwinian evolution.PLoS computational biology · 2022Article
- Evolutionary transition from a single RNA replicator to a multiple replicator network.Nature communications · 2022Article
- Innovation: an emerging focus from cells to societies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Article
- Nascent life cycles and the emergence of higher-level individuality.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The origin of evolutionary innovations is a central problem in evolutionary biology. To what extent such innovations have adaptive or non-adaptive origins is hard to assess in real organisms. This limitation, however, can be overcome using digital organisms, i.e. self-replicating computer programs that mutate, evolve and coevolve within a user-defined computational environment. Here, we quantify the role of the non-adaptive origins of host resistance traits in determining the evolution of ecological interactions among host and parasite digital organisms. We find that host resistance traits arising spontaneously as exaptations increase the complexity of antagonistic host-parasite networks. Specifically, they lead to higher host phenotypic diversification, a larger number of ecological interactions and higher heterogeneity in interaction strengths. Given the potential of network architecture to affect network dynamics, such exaptations may increase the persistence of entire communities. Our
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