CancerGram: Prediction of Anticancer Peptides

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: <>. For more information see: Burdukiewicz et al. (2020) <doi:10.3390/pharmaceutics12111045>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: biogram, devtools, pbapply, ranger, shiny, stringi, dplyr
Suggests: DT, ggplot2, pander, rmarkdown, shinythemes, spelling
Published: 2020-11-19
Author: Michal Burdukiewicz ORCID iD [cre, aut], Katarzyna Sidorczuk ORCID iD [aut], Filip Pietluch ORCID iD [ctb], Dominik Rafacz ORCID iD [ctb], Mateusz Bakala ORCID iD [ctb], Jadwiga SÅ‚owik ORCID iD [ctb]
Maintainer: Michal Burdukiewicz <michalburdukiewicz at>
License: GPL-3
NeedsCompilation: no
Language: en-US
Citation: CancerGram citation info
Materials: README
CRAN checks: CancerGram results


Reference manual: CancerGram.pdf
Package source: CancerGram_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): CancerGram_1.0.0.tgz, r-release (x86_64): CancerGram_1.0.0.tgz, r-oldrel: CancerGram_1.0.0.tgz


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