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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>.
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 |
DOI: | 10.32614/CRAN.package.CancerGram |
Author: | Michal Burdukiewicz [cre, aut], Katarzyna Sidorczuk [aut], Filip Pietluch [ctb], Dominik Rafacz [ctb], Mateusz Bakala [ctb], Jadwiga SÅ‚owik [ctb] |
Maintainer: | Michal Burdukiewicz <michalburdukiewicz at gmail.com> |
BugReports: | https://github.com/BioGenies/CancerGram/issues |
License: | GPL-3 |
URL: | https://github.com/BioGenies/CancerGram |
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: CancerGram_1.0.0.zip, r-release: CancerGram_1.0.0.zip, r-oldrel: CancerGram_1.0.0.zip |
macOS binaries: | r-release (arm64): CancerGram_1.0.0.tgz, r-oldrel (arm64): CancerGram_1.0.0.tgz, r-release (x86_64): CancerGram_1.0.0.tgz, r-oldrel (x86_64): CancerGram_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=CancerGram to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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