Package: Patterns
Type: Package
Title: Deciphering Biological Networks with Patterned Heterogeneous
        Measurements
Version: 1.7
Date: 2025-09-09
Depends: R (>= 3.5.0)
biocViews:
Imports: abind, cluster, e1071, gplots, graphics, grDevices, igraph,
        lars, lattice, limma, methods, Mfuzz, movMF, nnls, plotrix,
        SelectBoost, tnet, VGAM, WGCNA
Suggests: animation, Biobase, biomaRt, c060, CascadeData, elasticnet,
        glmnet, knitr, pixmap, R.rsp, rmarkdown, spls, testthat (>=
        3.0.0)
Authors@R: c(
	person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@lecnam.net", comment = c(ORCID = "0000-0002-0837-8281")),
	person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy@ehesp.fr", comment = c(ORCID = "0000-0002-4615-1512")))
Author: Frederic Bertrand [cre, aut]
        (<https://orcid.org/0000-0002-0837-8281>), Myriam
        Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>)
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: A modeling tool dedicated to biological network modeling
        (Bertrand and others 2020,
        <doi:10.1093/bioinformatics/btaa855>). 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 (Jung and others 2014,
        <doi:10.1093/bioinformatics/btt705>). Example of use with
        microarray or RNA-Seq data are provided.
License: GPL (>= 2)
Encoding: UTF-8
Collate: Patterns-package.R global.R datasets.R omics_array.R
        omics_network.R omics_array-omics_network.R omics_predict.R
Classification/MSC: 62J05, 62J07, 62J99, 92C42
VignetteBuilder: knitr
RoxygenNote: 7.3.3
URL: https://fbertran.github.io/Patterns/,
        https://github.com/fbertran/Patterns/
BugReports: https://github.com/fbertran/Patterns/issues/
Config/testthat/edition: 3
Config/pak/sysreqs: cmake libglpk-dev make libmagick++-dev gsfonts
        texlive libicu-dev libjpeg-dev libpng-dev libuv1-dev
        libxml2-dev libssl-dev
Repository: https://fbertran.r-universe.dev
Date/Publication: 2025-09-15 20:45:46 UTC
RemoteUrl: https://github.com/fbertran/patterns
RemoteRef: HEAD
RemoteSha: 053e13981fe1ec2f091e9706fc899b59f42772ab
NeedsCompilation: no
Packaged: 2026-06-12 08:23:06 UTC; root