AmpGram: Prediction of Antimicrobial Peptides

Predicts antimicrobial 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 AmpGram model is too large for CRAN and it has to be downloaded separately from the repository: <https://github.com/michbur/AmpGramModel>.

Version: 1.0
Depends: R (≥ 3.5.0)
Imports: biogram, devtools, pbapply, ranger, shiny, stringi
Suggests: DT, ggplot2, pander, rmarkdown, shinythemes, spelling
Published: 2020-05-31
Author: Michal Burdukiewicz ORCID iD [cre, aut], Katarzyna Sidorczuk [ctb], Filip Pietluch [ctb], Dominik Rafacz [aut], Stefan Roediger ORCID iD [ctb], Jaroslaw Chilimoniuk ORCID iD [ctb]
Maintainer: Michal Burdukiewicz <michalburdukiewicz at gmail.com>
BugReports: https://github.com/michbur/AmpGram/issues
License: GPL-3
URL: https://github.com/michbur/AmpGram
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: AmpGram results

Documentation:

Reference manual: AmpGram.pdf

Downloads:

Package source: AmpGram_1.0.tar.gz
Windows binaries: r-devel: AmpGram_1.0.zip, r-release: AmpGram_1.0.zip, r-oldrel: AmpGram_1.0.zip
macOS binaries: r-release (arm64): AmpGram_1.0.tgz, r-oldrel (arm64): AmpGram_1.0.tgz, r-release (x86_64): AmpGram_1.0.tgz

Linking:

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