AntAngioCOOL: Anti-Angiogenic Peptide Prediction
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 |
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