assertthat, crul, data.table, data.tree, digest, httr,
jsonlite (>= 0.9.8), sf, sp, stringr (>= 1.0.0), utils,
wellknown

c(person(given = "Martin",
family = "Westgate",
email = "martin.westgate@csiro.au",
role = c("aut", "cre")),
person(given = "Matilda",
family = "Stevenson",
role = "aut"),
person(given = "Dax",
family = "Kellie",
email = "dax.kellie@csiro.au",
role = "aut"),
person(given = "Peggy",
family = "Newman",
email = "peggy.newman@csiro.au",
role = "aut"))
The Atlas of Living Australia ('ALA') provides tools to enable users
of biodiversity information to find, access, combine and visualise data on
Australian plants and animals. 'galah' enables the R community to directly
access data and resources hosted by the ALA and other living atlases.
assertthat, crul, data.table, data.tree, digest, glue (>=
1.3.2), httr, jsonlite (>= 0.9.8), lifecycle (>= 1.0.0), rlang,
sf, stringr (>= 1.0.0), tibble, tidyselect, utils, wellknown
vcr (>= 0.6.0), covr, dplyr, knitr, magrittr, pkgdown,
rmarkdown, taxize, testthat

Biodiversity Data from the Living Atlas Community
The living atlas community provides tools to enable users
of biodiversity information to find, access, combine and visualise data on
plants, animals and fungi. 'galah' enables the R community to directly
access data and resources hosted by the living atlases.
assertthat, crul, data.table, data.tree, digest, glue (>=
1.3.2), httr, jsonlite (>= 0.9.8), lifecycle (>= 1.0.0), rlang,
sf, stringr (>= 1.0.0), tibble, tidyselect, utils
vcr (>= 0.6.0), covr, dplyr, kableExtra, knitr, magrittr,
pkgdown, rmarkdown, testthat

Genetic Algorithms for Multivariate Statistical Models from
Large-Scale Functional Genomics Data
c(person("Victor", "Trevino", role=c("aut","cre"), email="vtrevino@itesm.mx"),
person("Francesco", "Falciani", role=c("aut"), email="F.Falciani@liverpool.ac.uk"),
person("Copyright (C) The R Core Team", role=c("cph","ctb")),
person("Copyright (C) The R Foundation", role=c("cph","ctb")))
Victor Trevino [aut, cre],
Francesco Falciani [aut],
Copyright (C) The R Core Team [cph, ctb],
Copyright (C) The R Foundation [cph, ctb]
Build multivariate predictive models from large datasets
having far larger number of features than samples such as in
functional genomics datasets.
Trevino and Falciani (2006) <doi:10.1093/bioinformatics/btl074>.