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Tool

avidaR

Digital evolution is a branch of artificial life in which self-replicating computer programs—digital organisms—mutate and evolve within a user-defined computational environment. In spite of its value in biology, we still lack an up-to-date and comprehensive database on digital organisms resulting from evolution experiments. Therefore, we have developed an ontology-based semantic database—avidaDB—and an R package—avidaR—that provides users of the R programming language with an easy-to-use tool for performing complex queries without specific knowledge of SPARQL or RDF. avidaR can be used to do research on robustness, evolvability, complexity, phenotypic plasticity, gene regulatory networks, and genomic architecture by retrieving the genomes, phenotypes, and transcriptomes of more than a million digital organisms available on avidaDB. avidaR is already accepted on CRAN (i.e., a comprehensive collection of R packages contributed by the R community) and will make biologists better equipped to embrace the field of digital evolution.

Basic Information

Repository https://cran.r-project.org/web/packages/avidaR/index.html
Documentation https://gitlab.com/fortunalab/avidaR
Main publication (DOI) 10.7717/peerj-cs.1568 view
Contact email fortuna@ebd.csic.es
Authors/Maintainers Miguel Angel Fortuna, Raúl Ortega
Type of application R/python package
Programming languages R
Keywords Resources, Bioinformatics Software and Tools, Analysis packages (R, Python, etc.)

Technical details

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Software compatibility Linux, Mac, Windows
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Statistics
Unique users (last 12 months)
Unique users (since first release)
Software downloads (last 12 months) 1000-10000 (3452 as of 15/10/2026)
Software downloads (since first release) >10000 (16094 as of 15/10/2026)
Jobs submitted (last 12 months)
Jobs submitted (since first release)
Repository clones (last 12 months)
Repository clones (since first release)
Citations (last 12 months) <100 (~0 as of 15/10/2026)
Citations (since first release) <100 (0 as of 15/10/2026)
Early-stage researcher effort (development)
Early-stage researcher effort (maintenance)
Technician-supported effort (development)
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Total effort (maintenance)

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