DESCRIPTION

Package: CancerGram
Type: Package
Title: Prediction of Anticancer Peptides
Version: 1.0.0
LazyData: TRUE
Date: 2020-11-16
Authors@R: c(person("Michal", "Burdukiewicz", 
           email = "michalburdukiewicz@gmail.com", 
           comment = c(ORCID = "0000-0001-8926-582X"),
           role = c("cre", "aut")),
           person("Katarzyna", "Sidorczuk", 
           email = "sidorczuk.katarzyna17@gmail.com",
           role = c("aut"),
           comment = c(ORCID = "0000-0001-6576-9054")),
           person("Filip", "Pietluch", 
           email = "fpietluch@gmail.com",
           role = c("ctb"),
           comment = c(ORCID = "0000-0001-6218-9804")),
           person("Dominik", "Rafacz", 
           email = "dominikrafacz@gmail.com",
           role = c("ctb"),
           comment = c(ORCID = "0000-0003-0925-1909")),
           person("Mateusz", "Bakala", 
           email = "matibakala@gmail.com",
           comment = c(ORCID = "0000-0002-3213-2484"),
           role = c("ctb")),
           person("Jadwiga", "Słowik", 
           comment = c(ORCID = "0000-0003-3466-8933"),
           email = "jadwiga.slowik5@gmail.com",
           role = c("ctb")))
Description: Predicts anticancer peptides using random forests trained on the
    n-gram encoded peptides. The implemented algorithm can be accessed from
    both the command line and shiny-based GUI. The CancerGram model is too large 
    for CRAN and it has to be downloaded separately from the repository:
    <https://github.com/BioGenies/CancerGramModel>. For more information see: 
    Burdukiewicz et al. (2020) <doi:10.3390/pharmaceutics12111045>. 
License: GPL-3
URL: https://github.com/BioGenies/CancerGram
BugReports: https://github.com/BioGenies/CancerGram/issues
Encoding: UTF-8
Depends:
    R (>= 3.5.0)
Imports:
    biogram,
    devtools,
    pbapply,
    ranger,
    shiny,
    stringi,
    dplyr
Suggests:
    DT,
    ggplot2,
    pander,
    rmarkdown,
    shinythemes,
    spelling
RoxygenNote: 7.1.1
Language: en-US