Machine learning based package to predict anti-angiogenic peptides using heterogeneous sequence descriptors. 'AntAngioCOOL' exploits five descriptor types of a peptide of interest to do prediction including: pseudo amino acid composition, k-mer composition, k-mer composition (reduced alphabet), physico-chemical profile and atomic profile. According to the obtained results, 'AntAngioCOOL' reached to a satisfactory performance in anti-angiogenic peptide prediction on a benchmark non-redundant independent test dataset.
| Version: | 1.2 |
| Depends: | caret, rJava, RWeka, rpart, R (≥ 2.10.0) |
| Published: | 2016-08-01 |
| Author: | Babak Khorsand |
| Maintainer: | Javad Zahiri <zahiri at modares.ac.ir> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | AntAngioCOOL results |
| Reference manual: | AntAngioCOOL.pdf |
| Package source: | AntAngioCOOL_1.2.tar.gz |
| Windows binaries: | r-devel: AntAngioCOOL_1.2.zip, r-release: AntAngioCOOL_1.2.zip, r-oldrel: AntAngioCOOL_1.2.zip |
| macOS binaries: | r-release: AntAngioCOOL_1.2.tgz, r-oldrel: AntAngioCOOL_1.2.tgz |
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