Title: Example data for analysing OmniLog(R) Phenotype Microarray data
Author: Markus Goeker, with contributions by Lea A.I. Vaas and Johannes
Description: The package `opm' provides tools for analysing OmniLog(R)
Phenotype Microarray (PM) data as produced by the device
distributed by BiOLOG Inc. The package `opmdata' contains the
entire example dataset from Vaas et al. (2012), which has been

distributed by BIOLOG Inc. The package `opmdata' contains the

Title: Example data for analyzing OmniLog(R) Phenotype Microarray data
Description: The package `opm' provides tools for analyzing OmniLog(R)

Sikorski and Maria del Carmen Montero-Calasanz
Description: The package opm provides tools for analysing OmniLog(R)
distributed by BIOLOG Inc. and similar kinds of data such as
growth curves. The package opmdata contains the entire example
data set from Vaas et al. (2012), which has been removed from
opm due to its size, as well as the data sets from Wittmann et
al. (2013) and Montero-Calasanz et al. (2013).

Title: Package for analysis and visualization of metagenes
Description: This package translates microarray expression data into
metagenes and provides various visualizations and second level
Depends: R (>= 2.11.0), som, fastICA, pixmap, igraph, ape

Depends: R (>= 2.11.0), som, fastICA, pixmap, igraph, ape, biomaRt

Description: This package translates microarray expression data into metagenes and provides various visualizations and second level analyses.
Imports: som, fastICA, pixmap, igraph, biomaRt

Description: A decision support tool for prioritizing conservation projects.
Prioritizations can be developed by maximizing expected feature richness,
expected phylogenetic diversity, the number of features that meet
persistence targets, or identifying a set of projects that meet persistence
targets for minimal cost. Constraints (e.g. lock in specific actions) and
feature weights can also be specified to further customize prioritizations.
After defining a project prioritization problem, solutions can be obtained
using exact algorithms, heuristic algorithms, or random processes. In
particular, it is recommended to install the 'Gurobi' optimizer  (available
from <https://www.gurobi.com>) because it can identify optimal solutions
very quickly. Finally, methods are provided for comparing different
prioritizations and evaluating their benefits.
email='jeffrey.hanson@uqconnect.edu.au', role = c('aut', 'cre')),
Imports: utils, methods, stats, Matrix, magrittr (>= 1.5), uuid (>=
ggplot2 (>= 3.0.0), viridisLite (>= 0.3.0), lpSolveAPI (>=
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>