deepredeff: Deep Learning Prediction of Effectors (original) (raw)
A tool that contains trained deep learning models for predicting effector proteins. 'deepredeff' has been trained to identify effector proteins using a set of known experimentally validated effectors from either bacteria, fungi, or oomycetes. Documentation is available via several vignettes, and the paper by Kristianingsih and MacLean (2020) <doi:10.1101/2020.07.08.193250>.
| Version: | 0.1.1 |
|---|---|
| Depends: | R (≥ 2.10) |
| Imports: | Biostrings, dplyr, ggplot2, ggthemes, keras, magrittr, purrr, reticulate, rlang, seqinr, tensorflow |
| Suggests: | covr, kableExtra, knitr, rmarkdown, stringr, testthat |
| Published: | 2021-07-16 |
| DOI: | 10.32614/CRAN.package.deepredeff |
| Author: | Ruth Kristianingsih [aut, cre, cph] |
| Maintainer: | Ruth Kristianingsih <ruth.kristianingsih30 at gmail.com> |
| BugReports: | https://github.com/ruthkr/deepredeff/issues/ |
| License: | MIT + file |
| URL: | https://github.com/ruthkr/deepredeff/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | deepredeff results |
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