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 |
| Author: |
Michal Burdukiewicz
 [cre, aut],
Katarzyna Sidorczuk
[aut],
Filip Pietluch
[ctb],
Dominik Rafacz
[ctb],
Mateusz Bakala
[ctb],
Jadwiga Słowik
[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 |