#' @title Yeast protein localisations.
#'
#' @description A dataset containing the subcellular protein
#' localisations along with several amino acid sequence based metrics
#' used to make a classification of the localisation. `yeast` contains
#' the full dataset while `yeast_classes` is simply `class` collumn from
#' the `yeast` dataset as a vector, for convenience in the practical excercise.
#'
#' @format A data frame with 1484 rows and 10 variables:
#' \describe{
#' \item{seq}{Accession number for the SWISS-PROT database}
#' \item{mcg}{McGeoch's method for signal sequence recognition}
#' \item{gvh}{von Heijne's method for signal sequence recognition}
#' \item{alm}{Score of the ALOM membrane spanning region prediction program}
#' \item{mit}{Score of discriminant analysis of the amino acid content of
#' the N-terminal region (20 residues long) of mitochondrial and
#' non-mitochondrial proteins}
#' \item{erl}{Presence of "HDEL" substring (thought to act as a signal for
#' retention in the endoplasmic reticulum lumen). Binary attribute}
#' \item{pox}{Peroxisomal targeting signal in the C-terminus}
#' \item{vac}{Score of discriminant analysis of the amino acid content of
#' vacuolar and extracellular proteins}
#' \item{nuc}{Score of discriminant analysis of nuclear localization signals
#' of nuclear and non-nuclear proteins}
#' \item{class}{Experimentally observed subcellular localisations.
#'
#' Class Distribution. The class is the localization site.
#'
#' CYT (cytosolic or cytoskeletal) 463
#'
#' NUC (nuclear) 429
#'
#' MIT (mitochondrial) 244
#'
#' ME3 (membrane protein, no N-terminal signal) 163
#'
#' ME2 (membrane protein, uncleaved signal) 51
#'
#' ME1 (membrane protein, cleaved signal) 44
#'
#' EXC (extracellular) 37
#'
#' VAC (vacuolar) 30
#'
#' POX (peroxisomal) 20
#'
#' ERL (endoplasmic reticulum lumen) 5}
#' ...
#' }
#' @source Paul Horton & Kenta Nakai, ["A Probablistic Classification
#' System for Predicting the Cellular Localization Sites of Proteins"]
#' (https://www.aaai.org/Papers/ISMB/1996/ISMB96-012.pdf), Intelligent
#' Systems in Molecular Biology, 109-115. St. Louis, USA 1996.
"yeast"
#' Classes for the yeast data
#'
#' See the \link{yeast} help page for further info
"yeast_classes"
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