Title: Class-Focused Pattern Metric Comparisons using Simulation
Description: Provides tools for estimating composition and configuration parameters from a categorical (binary) landscape map (grid) and then simulates a selected number of statistically similar landscapes.  Class-focused pattern metrics are computed for each simulated map to produce empirical distributions against which statistical comparisons can be made. The code permits the analysis of single maps or pairs of maps.

Description: Provides tools for estimating composition and configuration parameters from a categorical (binary) landscape map (grid) and then simulates a selected number of statistically similar landscapes.  Class-focused pattern metrics are computed for each simulated map to produce empirical distributions against which statistical comparisons can be made. The code permits the analysis of single maps or pairs of maps.  Current limitation is for binary (classes 1, 2) maps that are 64x64 cells in extent.
Depends: R (>= 3.5.0), landscapemetrics, raster

Description: NOTE: This content is being migrated to the package ShapePattern to provide a comprehensive set of tools for shape and pattern analysis. All future maintenance will be in that package -- please update your links. This current package provides tools for estimating composition and configuration parameters from a categorical (binary) landscape map (grid) and then simulates a selected number of statistically similar landscapes.  Class-focused pattern metrics are computed for each simulated map to produce empirical distributions against which statistical comparisons can be made. The code permits the analysis of single maps or pairs of maps.  Current limitation is for binary (classes 1, 2) maps that are 64x64 cells in extent.

Title: Deciphering Biological Networks with Patterned Heterogeneous
Imports: abind, animation, Biobase, c060, cluster, elasticnet, glmnet,
gplots, graphics, grDevices, grid, igraph, jetset, KernSmooth,
lars, lattice, limma, magic, methods, Mfuzz, movMF, msgps,
nnls, pixmap, plotrix, SelectBoost, splines, spls, stats4,
Suggests: repmis, biomaRt, R.rsp, CascadeData, knitr, rmarkdown
Description: A modeling tool dedicated to biological network modeling. It allows for single or joint modeling of, for instance, genes and proteins. It starts with the selection of the actors that will be the used in the reverse engineering upcoming step. An actor can be included in that selection based on its differential measurement (for instance gene expression or protein abundance) or on its time course profile. Wrappers for actors clustering functions and cluster analysis are provided. It also allows reverse engineering of biological networks taking into account the observed time course patterns of the actors. Many inference functions are provided and dedicated to get specific features for the inferred network such as sparsity, robust links, high confidence links or stable through resampling links. Some simulation and prediction tools are also available for cascade networks. Example of use with microarray or RNA-Seq data are provided.