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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, r-oldrel (x86_64): AmpGram_1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=AmpGram 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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