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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
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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 |
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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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